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CONTENTs FX

05 Editor’s notE

MACroEConoMiCs06 Return to Valuation: how CPi-based Purchasing Parity Power can make it easy to derive longterm valuations in FX markets

strAtEGY18 Forex Leverage: Friend or Foe? the risks of using a high degree of leverage on the Forex markets

30 Using Oscillators as trend following indicators: an example of how the stochastic can be used to identify trends on various timeframes

MArKEt WAtCH21 If...: when managers of traditional UK financial institutions start looking at the FX market

oPtions25 FX Options Primer: using options as a safer means of hedging or speculating. Part 1.

intErViEW38 robert Marcellus FX Manager explains how he reached a +18,48% performance in 2008

trAdinG sYstEMs33 Building Robust FX Trading Systems, by identifying and exploiting a small edge, as many times as possible

FoCUs47 Bonds: why are bonds attracting retail and hign net-worth investors?

tECHniCAL AnALYsis49 The Magic of Elliot Wave 23 Majors report54 Technical Outlook

intErnAtionAL dAtA57 FX Spot Monitor58 Central Bank Rates 59 Economica Data - FX Poll 60 Markets View

37 GLossArY

UnConVEntionAL MonEtArY PoLiCiEs:how policy makers are shaping the currency markets through confusing sometimes frantic decisions

12

GrAMMAtiCAL EVoLUtion:

implementing a trading model through a promising evolutionary computing approach38

FUndAMEntALs oF trAdinG PsYCHoLoGY:

Part 1:getting prepared to cope with the laws of Quantum mechanics

09

FX TRADER MAGAZINE April-May 2009 03

Alessandro Balsotti, is head of FX trading in Abax Bank and covered the same role previously in Banca Caboto. For several years he has been the FX market-maker of italian Lira, Greek dracma and Czech Crown in JP Morgan.

Ben Brown, has worked in the FX and Money Markets for 15 years with some major interbank brokers and at one the UK’s largest independent Broker dealers,.With a knowledge of the market from tier 1 to tier 3 Ben has a fundamental and somewhat lighter approach to the FX market.

Grace Cheng is a seasoned forex trader, and founder and editor of www.dailyMarkets.com, a leading new York-based financial blog. she is also author of “7 Winning strategies For trading Forex” (2007, Harriman House, UK), and the creator of the online PowerFX Course.

Rodolfo Festa Bianchet is trainer and traders coach. He is CEo of riflexo Ltd and founder of trendrisk expert system. His analysis on Forex have been published on down Jones Markets private network for over 10 years. He is regularly invited to run seminars on trading Psycholoy at various financial and trading conferences.

D. Roy Fraser, is the Managing director of incapital Europe Limited, the investment bank that runs a platform providing regulated financial intermediaries with investment-grade bonds, which can be further explored at incapital.com, internotes.com and structuredinvestments.com

John Hydeskov, is senior FX strategist at danske Bank FX research team. John joined danske bank in 2007 and has worked with G10 FX strategies. He previously worked for Bank of England Exchange rate team and danis national Bank FX liquidity team.

Steve Jarvis, from traderMade international has over 20 years’ experience of providing technical analysis to FX professionals. Formerly Chief technical Analyst at MCM Currencywatch and informa Global Markets, steve now heads the technical

analysis at interpretA, tradermade’s newly launched technical analysis service.

Ashif F. Jiwani, is Head of derivatives trading at saxo Bank Capital Markets (Asia). He was previously global head of FX options business at CiBC and has spent 8 years at scotia Bank and CiBC trading currency derivatives in a market making capacity.

JW Partners is an independent FX solution provider, based in Milan, with a strong FX specific know-how. JW supports institutional investors and HnWi in building quality FX multimanager portfolios, and FX underlying structures.

Caspar Marney, started his trading career, as a spot currency trader and technical analyst with HsBC in London. He then moved to sBC Warburg (later UBs) as a proprietary trader and global head of technical analysis for FX and precious metals, where he became one of the bank’s most successful traders and a regular commentator on financial television.

Maurizio Milano, began his career as forex dealer in 1995. He started the technical analysis department at Banca sella Group. He teaches technical analysis at the University of turin, italy. His contributions can be found in the most renowned italian financial newspapers and televisions: Borsa&Finanza, il sole24ore, il Corriere della sera, Class-CnBC, radiorai1. He is member of siAt (the association of the italian technical analysts) and iFtA (the international Federation of technical Analysis).

N.Ramakrishnan, better known as ramki, is a professional banker and has been in the treasury business since 1984. He has been extensively quoted in telerate and reuters as well as finance journals and newspapers of repute. ramki writes a web blog www.tradewithramki.com and has a website www.wavetimes.com

Luca Taroni, is a quantitative trading system developer. Luca is head of research & development at Luxorlab.

CONTRIBUTORSFX

Editor : Emmanuelle Girodet

[email protected]

Advertising manager:Monique Atlan

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Webmaster:Hristo Katzarski

[email protected]

Graphic design: Preslav dobrev

Editorial support:Lorenzo Lorenzi

Luca di Bari

trading carries a high level of risk, and may not be suitable for all investors. The objective of FX trader Magazine is to give readers the tools, training and information which will help them be better prepared to trade on the foreign exchange. However, any analysis, news, research, strategy, or other information contained on this magazine is provided as general market information and does not constitute investment advice.

FX trader Magazine, will not accept liability for any loss or damage, including without limitation to, any loss of profit, which may arise directly or indirectly from use of or reliance on such information.

Subscriptions:www.fxtradermagazine.com

04 FX TRADER MAGAZINE April-May 2009

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FXEDITOR’s note

since the beginning of the credit crisis, the currency markets have registered unprecedented levels of volatility, increasing from 5% to over 20%. the current economic calendar, full of market-moving events, tends to heighten uncertainty and increase volatility even further.

For most professional and private Forex traders, this means growing concerns about risk hedging and money management. Heads of FX departments at main global banks are mostly concentrating on risk management these days, whereas more and more private clients ask for currency hedging programs, or look towards less risky instruments such as bonds or FX derivatives in order to lower risk exposure in the short and long term.

But despite the high level of volatility and the gloomy international perspective for 2009 (“a dangerous year”, as robert

Zoellick, President of the World Bank, defined it recently), there has been significant growth in the use of FX instruments over the past year.

the FX market has been defined as “red hot” by market experts. it is one of the very few markets going in countertrend in today’s global economic crisis. Average turnover grew by an unprecedented 71% from 2004 to 2007, to $3.2 trillion per day, and volumes increased of 40% between April 2007 and April 2008. Electronic transactions represent a growing proportion of all trades, and are expected to rise to more than 75% by 2010. spot transaction daily volumes have grown to over 1 billion euros, from which 15% are traded by retail customers.

Consequently, the retail FX industry is expanding rapidly. the number of online brokers, training services, education material, and FX related websites

are growing every day to support the increasing retail demand. More and more financial institutions are looking at Forex with greater interest and major banks are partnering with established FX brokers.

FX is often defined as a very accessible

and easy to understand market, offering high return opportunities, high margins, low investment capital and the possibility to trade 24 hours a day on a reasonably limited number of market instruments. in other words the new Far West... true and false. successful FX traders are highly trained and prepared, and most of them are professional traders. they keep reading, exercising, planning in order to keep their own edge on the market.

FX trader Magazine is born to answer the growing need for sharp market experts’ opinions and analysis, and ground-up training on currency investment techniques and strategies. this first edition analyses the impact of fundamental macroeconomics aspects on currencies and focuses on a series of educational articles covering options, trading systems and trading psychology. in the next editions, we will start a series of market participant interviews and trading resources reviews. our objective is to give traders all the necessary tools to become successful during high volatility periods, strong market trends and trading ranges.

FX trader Magazine will listen to you, help you and welcomes you!

Emmanuelle Girodet

Welcome to red Hot FX


one of the cornerstones in international economics is the theory of purchasing power parity (PPP), which simplified states that price levels in two countries should be identical after converting prices into a common currency. PPP is an appealing approach for many long-term investors in currency markets as it serves as an anchor when exchange rates are moving rapidly, as at present. But with various PPP measures, which one should we look at and why? Which currencies are farthest away from equilibrium levels and may therefore be subject to weakening or strengthening going forward? Has the past year’s sharp movements erased the misalignments in the G10 currency universe and are we now close to equilibrium?

Basically, two versions of PPP exist – an absolute version and a relative one. Absolute PPP theory states that a basket of goods costs the same at home and abroad if goods prices are converted into a common currency. to put it differently, PPP assumes that purchasing power is equal between countries. By contrast, relative PPP theory does not compare levels of purchasing power at home and abroad, but rather

focuses on changes in purchasing power. Accordingly, relative PPP states that inverse changes in the nominal exchange rate that offset inflation differentials between countries are such that the PPP ratio remains constant. the validity of absolute PPP theory therefore implies the validity of relative PPP theory, but not vice versa.

the PPP theory is based on the law of one price and there are a number of caveats to the theory. First, transportation costs, barriers to trade and other transaction costs can be significant. second, there must be competitive markets for the goods and services in both countries. third, the law of one price

only applies to tradable goods – immobile goods such as houses, and many services that are local, are

of course not traded between countries. this might elucidates why PPP explains movements in exchange rates over short or medium time periods quite poorly. But over very long periods of time PPP does seem to have better luck in explaining FX movements. However, rogoff (1996) found that the speed of convergence to PPP is extremely slow; deviations appear to dampen out at a rate of roughly 15%.

Purchasing Power Parity serves as an anchor when exchange rates are moving rapidly

PPP and the return

to valuation


FX MACROEconomics

FXMACROEconomics


the simplest way to calculate purchasing power parity between two countries is to compare the price of ‘standard’ goods that are identical across countries. the Economist publishes a light-hearted version of PPP: ‘the Big Mac index’ which compares the price of a Mcdonald’s hamburger around the world. this index suggests that a norwegian Big Mac is too costly compared with an Australian one.

For practical FX analysis, there are a number of characteristics we would ideally like our PPP-estimates to possess: First, a good PPP estimate encompasses a large number of goods and services – not just the price of a burger. Accordingly, CPi- or PPi-based measures are preferred. second, we need PPP estimates to be comparable – the best way to ensure the use of price data from a single source, measure exchange rates at the same date and time, and evaluate estimates over the same base period. third, availability is a must. if estimates are difficult to get hold of and access is cumbersome, most investors look elsewhere for

alternative valuation measures. Finally, we like it if markets agree on a common measure. this equates to less confusion and less potential misunderstanding.

An easily accessible way to get a quick overview on PPP estimates is via Bloomberg’s PPP <Go>. if one accepts the pre-chosen base period ( January 1982-June 2000) it is convenient to dive into a small PPP

study and many insights are obtained quickly and straightforwardly.

By looking at long-term valuation against the Us dollar in the G10 universe derived from CPis we observe that danish krone, euros and swiss francs are currently the most overvalued currencies while sterling , the new Zealand dollar and especially the swedish krona are the most undervalued. this picture is, however, very different compared with one year ago, when all G10 currencies were overvalued against the Us dollar, except the yen. We have, in

FX MACROEconomics

other words, seen a huge adjustment toward long-term estimates in the past year. the picture is very similar when using PPis instead of CPis. this makes us conclude that we gain little additional insight when applying a different price metric within this framework.

on the one hand, we obser ve that both the average total actual and absolute under- and over-va luations within the G10 universe have fallen. specifically, the average total actual valuation misalignment is currently close to zero, implying the G10 universe is close to equilibrium. this is not the same as all spot rates being at their equilibrium levels, but merely an indication that the sum of deviations from equilibrium is small at present. this is also confirmed by the fact that the average total absolute deviation is below its historical average.

on the other hand, we obser ve that differences

among actual and absolute under- and over-valuations, measured by standard deviations, have risen and both are above historical averages. Additional to that, differences between the largest and smallest valuation misalignments have similarly risen and are likewise above historical averages.

to sum up, a CPi-based PPP estimate, which uses a long-run averaging m e t h o d o l o g y , makes it easy to derive long-term valuations

in FX markets. According to PPP analysis, EUr/sEK could very well see a downward swing in excess of 40% if the spot rate adjusts to the current PPP estimate. such a large move might seem outrageous, but it would in fact not be far greater than the spike previously seen in EUr/GBP. triggers for a downward move in EUr/sEK could be an improvement in risk aversion, a pick-up in equity performance and a bettering of global economic growth prospects. We are not able to draw any strong conclusions as to whether the G10 currency universe is in equilibrium or not, as statistical measures point in various directions. We are, however, able to state that previous misalignments have become considerably smaller while deviations among under- and over-valuations have risen lately and now remain above historical averages.

John Hydeskov

a CPi-based PPP estimate can make it easy to derive longterm valuations in FX markets



Most traders have a limited knowledge of trading’s fundamental rules, either from a psychological or a methodological point of view. This can lead to increasing loss probabilities on the markets, as well as deep and constant psychological damage.

recent studies have proved that professional trading has a lot in common with professional sports activity and competition. in fact, sport coaching and training experience can be replicated and implemented to train financial traders. in any kind of sport, a series of fundamental exercises, which should be learned and practiced regularly, are necessary to reach competition level and become successful. For example, in basketball, some fundamental exercises to work on would include: rebound, left shot, right shot, dribble, pass, shot in

suspension, etc.

trading fundamentals are:

• Market• Mind• Method• MoneyManagement

to be successful in trading, it is necessary to understand and learn these fundamental theories and, at the same time, learn a method of thought which will help implementing them in trading activity.

The knowledge and implementation of these 4 fundamentals is probably what makes the difference between successful and unsuccessful traders. traders who make profits continuously and in the long run, have consciously or unconsciously:

1. understood their market and the effects that it could have on their mind;

2. eliminated, or learned how to cope with the negative effects of trading;

3. found a methodology - often through a thorough, long lasting research, and demanding practice - which gives them a probabilistic edge on the market. Generally, successful traders have found a method which is adapted to their personality and best capabilities (to use a marketing term: they have found their own trading niche);

4. implemented money and risk management strategies which allowed them to reach point 2 (eliminate the negative effects) and contributed to generate profits on a regular basis.

Part 1: The Market Accepting constant market changes and uncertainties

Fundamentals of successful trading

PSYCHOLOGY FX

the objective of this series of articles is to explain the fundamentals of trading and how to implement a training program which will highly increase the probabilities of success, to anyone who has a passion for trading and wants to be successful at it.

in this first article, we’ll start by analyzing the market and its specific characteristics. We will see how the implementation of certain mental strategies, which usually lead us to success in our every day life, can be dangerous in the trading activity.

in any financial market, the creation of a market price occurs through the confrontation between buy and sell decisions. it is made of individual decisions (billions of them), which generate a continuous and collective decisional stream. this stream is what defines the price of a specific market instrument at a specific time. As traders, we have the possibility to continuously make multiple decisions (based on expectations) about: the market direction, the amount of invested capital, loss limit levels, the duration of a trade, etc., with the possibility to modify our decisions any time.

these decisions aren’t only based on rational elements (as developed in the theory of Efficient Market Hypothesis or EMH) but, also on irrational and unconscious elements, which continuously

invite us to change our mind, sometimes very rapidly.therefore the market is always moving , always changing. it has no defined structure and offers high profit and loss opportunities. in a fraction of a second markets can go from apparent quietness and stability to extreme speed

and turbulence. this specific market characteristic is often ignored or underestimated by traders. But having to cope with a completely unstructured, fluid and ever changing environment is not something that we are used to. it’s like being projected into a world without laws, similar to the motion of atoms in a quantum mechanics system.

Let’s take for example, a very simple

activity such as sitting down. in a world regulated by quantum mechanics rules, this simple action could become extremely complicated and risky, for anyone used to living in our “normal” world. What would happen if i sat down? sometimes the chair would remain in the same position, both in

terms of space and time. sometimes the chair would disappear and reappear in another place at an unexpected time. so the simple action of sitting down, could actually become very difficult if i continued to refer to my usual model of thought. so to be able to sit down in a world regulated by quantum mechanics, i’d have to learn a completely different way of thinking and acting. otherwise, i’d be very inefficient.

a world regulated by the laws of quantum mechanics


PSYCHOLOGYFX

PSYCHOLOGY FX

As human beings, one of our main purposes is to create mental structures for ourselves which will bring us security and stability. And this is the main problem that traders have when confronting the financial markets.

We are not used to interacting with an environment which is mainly ruled by change and uncertainty. An environment where the mental and decisional processes of all market participants are constantly changing .

traders’ search for the Holy Grail- in other words the indicator or the theor y which will systematically forecast market movements - is actually only an attempt to eliminate constant market uncertainty.

therefore the first fundamental rule of the market is to accept changes and market uncertainties ( in other words accept risK). there is no other way to sur vive the financial markets than to accept this obvious rule. And it is a fundamental rule precisely because it is obvious. Easy to understand from a theoretical point of view, much more difficult to put into practice.

Accepting change and uncertainty doesn’t mean having a confused or insecure mind-set and attitude. on the contrar y, understanding that fluctuations

depend on mental processes and decisions, which can var y depending on an infinite number of unpredictable factors, allows us to eliminate all the mental mechanisms which generate pain (these will be developed in subsequent articles).

the absence of pa in chang es our perception and g ives us the possibi l i t y to be obje ctive and rationa l . obje ctive perception is f undamenta l in trading , a s traders have to re cog nize market patterns . therefore , a rationa l and obje ctive mind set wil l help us de velop a rationa l de cis ion ma king model , which is not base d on emotions . Acknowle dg ing the fact that markets are unpre dictable and accepting trading risk i s - according to me - what ma kes the difference bet we en

a successf ul and unsuccessf ul trader.this state of mind is an ability (or sKiLL) which any trader should reach before he/she can start becoming profitable constantly and in the long run.

Rodolfo Festa Bianchet

In the next articles, the author will cover the importance of the mind, the method and the money management. He will develop each of these aspects giving a practical training methodolog y to improve in the long run in each of these fundamental areas.


UnConVEntionAL MonEtArY PoLiCiEs

“We have two classes of forecasters: those who don’t know, and those who don’t know they don’t know “

John Kenneth Galbraith

dollar and Yen: sharing the same fate?

norway:a real safe-heaven ?

FX MACROECONOMICS


FXMACROECONOMICS

T he correlation between FX and risky assets is changing. if warned in advance that

the stock exchanges in the Western world would have lost on average 20% (with the notable exception of italy - around 30% - a performance in line with countries to the outskirts of Eastern Europe) in the first nine week of the current year, the FX trader would not have hesitated to

buy Jpy, Chf and Usd. in fact, facing a macro scenario with a continuous and rapid deterioration faithfully accompanied by the descent of the stock market, the only currency respecting the correlations we were accustomed to in recent months, maintaining its status as a ‘safe-haven’ and resisting for quite a while the constant attacks of skeptics, has been the dollar.

in the wake of stocks hitting new lows (s&P at 666, a number so full of symbolism on March 6th), Eur/Jpy and Eur/Chf were not much changed from the beginningof the year. the dollar, on the other hand, enjoyed an increase of between 5% and 10% against other major currencies and well above 10% against emerging currencies (we could include nzd as well).


Let’s take a step back. The first weeks of the year brought a few clear starting points for market analysis.

- The macro data leave no doubt on the vicious cycle in which the financial crisis has precipitated the real economy. to imagine a rebound in the second half of 2009 that goes beyond a limited positive effect coming from hyper-aggressive fiscal and monetary policies, would be at the moment, an act of faith.

- The activism of policy-makers, in both fiscal and monetary camps, has developed in a more and more frantic and confused manner, culminating in timothy Geithner’s presentation of a financial system rescue plan, February 10th, a speech universally recognized (at best) as a ‘communications disaster’. sadly, looking over our shoulder, we would recognize the rescue of Bear stern as the last economic policy move, now one year old, capable of generating a significant (bear) market rally. in this sense Paulson tArP/tALF, the new obama administration fiscal package, but also, to be honest, the announcement of a massive tax plan by the Chinese, have all failed.

- Consequently market rebounds that could honor the definition of ‘rally’ (like the one now in place since early March) seem to take inspiration more from oversold conditions and excessive pessimism (we could say desperation) than from the actual perception of improvement in the macro picture or from the (perceived) quality of policy activity.

Dollar and Yen: sharing the same fate?

The dollar has strengthened markedly during January. The Eur/Usd has gone from 1.4000 to 1.2700. subsequent lows at 1.2514 on February 18th and 1.2457 on March 4th represent small progress, unable to attack the low of recent years (1.2330, october 28th 2008). For the dollar, January has been a golden month also against other currencies. However, it should be noted that with the exception of Cable (1.3505 on January 23th), the dollar high has mostly been achieved in

February or March: Usd/Chf 1.1966 (March 12th), Usd/Cad 1.3064 (March 9th), Aus/Usd 0.6248 (February 2nd), nzd/Usd 0.4900 (March 4th). in all these cases the story is quite similar: the lows of various currencies against the dollar, reached in the last quarter of 2008 in the weeks following the Lehman fall, have been, after a violent rebound in december, approached again, and in some cases marginally exceeded (more significantly for Gbp/Usd). The impression, at least graphically, is quite vivid: dollar appreciation encounters relevant obstacles coming close to levels of 1.25 (Eur/Usd), 1.30 (Usd/Cad), 0.6200 (Aud/Usd), 0.5000 (nzd/Usd), 1.2000 (Usd/Chf ).

The yen story is different and in some ways more interesting. in January, Jpy has proved itself an even stronger currency than the rampant U.s. dollar: on January 21st the yen is able to hit again the level reached on december

FX MACROECONOMICS

Chart 1: Jpy and stock markets decorrelate


17th (87.12). such a progress is even more pronounced against the Euro (112.10 beats the previous low of 113.63 in october). The usual correlation with a stock market deeply under water seems strengthened. in fact, after a period of lateral trading from mid-February, the trend reversal is remarkable: the upward pressure on the Japanese currency resulting from the continued reduction of leverage in yen-funded positions is slowing and the inverse relationship of the currency with the price of risky assets is falling too. data on yen borrowing of foreign banks from the Japanese banking system (back to 2005 levels) suggest that much of the global carry-trade has now been dismantled. in a world where global trade has suffered a sharp correction, the Japanese economy, traditionally based on the export sector and perfectly placed in the ‘supply-chain production’ of East Asia, has recently seen a dramatic deterioration of the macro scenery (data for GdP

and export have been significant in this sense). Moreover, on the political side, the last few years post Koizumi tentative reformist period (with weak statesmen of the likes of Abe, Fukuda and Aso) has been frankly disappointing, culminating in the grotesque appearance of Minister nagakawa drunk on global broadcast. Without the support of deleveraging (and in the short term of the repatriation for Japan’s fiscal year end) the yen is likely to return to its old forgotten status of a ‘cyclic’ currency in a unfavorable macro environment. Usd/Jpy price action flying in a few sessions in the second half of February, from 90 to almost 100 seems to prove it.

Abrand new acronym: QE. 2007 and 2008 have taught us to appreciate (so to

speak) he synthesis skills achieved by financial acronyms (Cdo, ABs, rMBs, CLo… then steaming ahead with tArP, tALF and other similar

amenities). More recently we have experienced the maximum contraction possible with only two letters: QE, the recent universal abbreviation of Quantitative Easing. When official interest rates get close to 0 (ZirP, another beautiful acronym = Zero interest rate Policy), this conceptual category (QE) includes all the measures that central banks plan to put in place to try to prevent collapsing consumption and investment activity to feed a vicious deflation spiral, trying in essence to provide the private sector (consumers and corporates) sufficient liquidity to slow and hopefully reverse such a process.

Without embarking on a scholarly

disquisition on risks and opportunities of QE (the discussions without clear cut conclusions on Bank of Japan QE between 2002 and 2006 are still far from resolved), it is instead quite easy to judge the FX impact of similar measures recently adopted by some central banks.

- Thursday, March 5th. Bank of England MPC (Monetary Policy Committee) at the end of its monthly

FXMACROECONOMICS


meeting publishes the contents of letters exchanged between the Governor and the Prime Minister, detailing the authorized plan to purchase securities aimed at increasing liquidity in circulation and to avert the danger of deflation. the plan consists of buying up to 150 billion pounds of public debt bonds and private securities (100+50), 75 billion of which is to be made in the subsequent three months. in the two weeks following the event, the pound weakens against the euro from 0.8850 to 0.9490. FX movements of two successive events of similar tenor will be much less gradual.

- thursday, March 12th. the swiss national Bank after their monthly meeting airs their decision to purchase corporate bonds and most importantly to purchase foreign currency in order to expand domestic money in circulation. Words are immediately followed by facts: according to rumors between 5 and 10 billion swiss francs are sold by the central bank against euro and the dollar following the announcement. in the most violent intraday move Ever, the franc weakens by evening from 1.4800 to 1.5400 against the euro.

- Wednesday, March 18th. the Federal open Market Committee discloses a plan of 300 billion dollars purchases of U.s. treasuries to be executed by auction in the next six months and increases their purchasing program of agency (Fannie and Freddie) mortgage backed securities (MBs) from 500

to 1,250 billion and agency debt from 100 to 200 billion. Following a Pavlovian reaction, the dollar loses almost 5% against major currencies in the next 24 hours. the market appears shocked, still, back in november 2002, in the famous ‘helicopter speech’ (www.f e d er a l re s er ve . g o v / b o a rd d o c s /speeches/2002/20021121/default.htm), Ben Bernanke, a scholar of the Great depression, had warned us: “the U.s. government has a technology, called a printing press (or, today, its electronic equivalent), that allows it to produce as many U.s. dollars as it wishes at essentially no cost. By increasing the number of U.s. dollars in circulation, or even

by credibly threatening to do so, the U.s. government can also reduce the value of a dollar in term of goods and services, which is equivalent to raising the prices in dollars of those goods and services. We conclude

that, under a paper-money system, a determined government can always generate higher spending and hence positive inflation.” they do look determined ...

on the same note we can add that a few weeks before, the market, after discovering that one of the members of the Board of the riksbank, the swedish central bank (rolf Larsson) had openly discussed the option to purchase foreign currency (i.e. FX intervention) as the most effective way to combat the spectre of deflation, did push the swedish krona to new lows against the euro (11.7925 March 6th, before a significant recovery).

it cannot be missed that in the

absence of rate differentials and with the lack of asynchronous cycles of monetary policy, the approach to the QE by the various central banks is providing important elements in the analysis and prediction of FX movements.

FX MACROECONOMICS


Chart 2: March 12th 2009, worst day ever for Swiss franc

http://www.federalreserve.gov/boarddocs/speeches/2002/20021121/default.htm




Norway: a real safe-heaven ?Among the G10

currencies, best performer year to date is certainly the norwegian crown. The appreciation is around 10% on average, certainly not negligible. At current levels against the euro (8.6500) the crown has recovered about two-thirds of the inevitable losses following Lehman collapse, culminating in the all-time low at 10.1700 just on Christmas Eve. The explanation for this excellent rebound resides in a number of factors:

- The economic data have revealed a deteriorating situation in the wake of the global recession but less dramatically so than the ‘macro disaster’ of most neighboring European nations. Growth has been close to zero in the last two quarters of last year. A possible contraction in this first half of 2009 looks minor compared to the other western economies.

- Accordingly monetary policy has been lacking so far the aggressiveness and pathos nowadays usual for other central banks (the rates at 2.50%, or even 2% after a forecasted new cut at next meeting on March 25th, are the highest among developed countries, Australia and new Zealand aside).

Besides, the need to implement QE policies is not been mentioned at all.

- despite being an oil exporting country, the reinvestment of most (95%) of the oil revenues abroad through the oil Fund has made the currency less sensitive to fluctuations in raw material prices (i.e. last few months collapse) compared to other exporting countries such as russia or Mexico.

- A banking industry of small size in GdP terms (ratio bank assets/GdP below 100%, figures which compares, to pick the most extreme cases, to more than 600% in Belgium and switzerland according to BCA data research) and less exposed to highly critical areas (like swedish banks to Baltics or Austrian banks to Eastern Europe).

Alessandro Balsotti Chart 3: the nice rebound of the Norwegian Krona

FXMACROECONOMICS


The word “leverage” is often associated with trading, and this magic word is more hyped up in the world of Forex trading compared to the trading of other financial instruments. Many people, especially those who are new to Forex and those who don’t really have an idea of how it works, perceive Forex trading to be extremely risky because Forex can be a highly leveraged instrument.

What Is Leverage?

First of all, let me define the basic concept of leverage. Leverage involves borrowing a certain amount of the money needed to invest in something. in the case of forex, that money is usually borrowed from a broker. Forex trading does offer high leverage in the sense that for an initial margin requirement, an investor can build up, and control a huge amount of money.

to calculate the leverage you are

currently using, simply divide the total face value of your open positions by your trading capital (see Figure 1). For example, if you have $10,000 in your account, and you open a $100,000 position (which is equivalent to 1 standard lot), you will be trading with a 10 times leverage on your account (100,000/10,000). if you trade 2 standard lots which is worth $200,000 in face value with $10,000 in your account, then your leverage on account is 20 times (200,000/10,000).

Is Leverage Necessary In Forex?

in trading, we monitor the currency movements in pips, which is the smallest change in currency price, and that could be in the second or fourth decimal place of a price, depending on

the currency pair. However, currency exchange rates move very little on the surface as their movements are merely fractions of a cent. That is why currency transactions must be carried out in big amounts so that these minute price movements can be translated into decent profits when magnified through the use of leverage. When you deal with a large amount like $100,000, small changes in the price of the currency can result in decent-sized profits or losses.

Many retail Forex brokers offer a sizeable amount of leverage to their customers. some offer 50 times leverage, while a increasing amount of them even allow up to 400 times leverage for standard-sized or mini-sized accounts. the good thing is that you, the customer, are often given the flexibility to select your leverage amount based on your trading style, personality and money management preferences.

Forex Leverage Friend or Foe?

FX STRATEGY


Higher Leverage Equals More Risk

i must emphasize that leverage can be your best friend or your worst foe. Leverage can either magnify your profits or magnify your losses. You can stand to make a huge profit if the trade goes your way, but if the trade ends up going against you, you can equally stand to lose a huge amount. That said, the higher the amount of leverage on capital that you use, the higher the risk that you will assume.

Let me illustrate this point with an example (see Figure 2).

Both trader Average and trader smart have a trading capital of $10,000, and they trade with a broker that requires a 1% margin deposit. After doing some trade analysis, both of them come to the conclusion that Usd/CHF is hitting a top, and should be declining in value. Therefore, both of them short the Usd/CHF at 1.2200.

trader Average, feeling quite aggressive, decides to apply 50 times leverage on this trade by shorting $500,000 worth of Usd/CHF (50 x $10,000) based on his $10,000 trading account. That $500,000 worth of Usd/CHF equals to 5 standard lots (since 1 standard lot is $100,000). His margin deposit for this trade is $5000 (which is 1% of $500,000). At the time when Usd/CHF stands at 1.2200, 1 pip of Usd/CHF for 1 standard lot is worth approximately $8.20, so 1 pip of Usd/CHF for 5 standard lots is worth approximately $40. if Usd/CHF goes up instead to 1.2300, trader Average will lose 100 pips on this trade, which is equivalent

to a loss of $4000. This single loss represents 40% of his total trading capital.

trader smart, being a more conservative trader, decides to apply a 5 times leverage on this trade by shorting $50,000 worth of Usd/CHF (5 x $10,000) based on his $10,000 trading account. That $50,000 worth of Usd/CHF equals to just 0.5 standard lot (since 1 standard lot is $100,000). His margin deposit for this trade is $500 (which is 1% of $50,000). if Usd/CHF goes up instead to 1.9600, trader smart will lose 100 pips on this trade, which is equivalent to a loss of $410. This single loss represents 4.1% of his total

trading capital.

Both trader Average and trader smart have set their stop-loss at 100 pips for this trade, but look what happens to trader Average’s trading account? His account equity is reduced by half based on this one trade. if he applies the same amount of leverage and sets the same stop-loss in pips for the next trade, and again loses, his entire trading account will be wiped out.

on the other hand, trader smart, simply by using less leverage, has managed to preserve almost 96% of his trading capital, even though he has also set a 100-pip loss for this trade.

content * content * content FXSTRATEGY


Many trading accounts have been wiped clean from traders who have applied a large amount of leverage on their trades. Either they do not know that excessive leverage can completely destroy one’s trading capital in a blink or they flatly ignore that.

My Broker Offers 400 Times Leverage. Should I Seize That Opportunity?

no. no. And no – at least if you have no intention of losing your hard-earned money in quadruple-quick time. Let me illustrate with some figures.

Let’s say you have a trading account size of $10,000.

A 400 times leverage would mean that you can open a position that is worth 400 times of your trading account. if you are thinking of trading Usd/JPY, a 400 times leverage allows you to trade $4,000,000 worth of Usd/JPY, which is equivalent to a whopping 40 standard lots. At the time of writing, 1 pip of Usd/JPY for 1 standard lot costs $8.47. Therefore, 1

pip of Usd/JPY for 40 standard lots will cost $338.80. Based on an account size of $10,000, it will take a mere 30-pip loss for you to see nothing left in the account. of course, if the trade does go your way, and you manage a 30-pip gain, your profit will amount to about $10,100.

novice traders will think about the potentially large profit, whereas experienced traders will see the potentially large loss as a bright red warning sign. Most experienced traders do not use more than 10 times leverage in their trading, and even that is more than what most fund managers are allowed to use.

The question is not how much your forex broker allows you to leverage, but how much you should leverage.

Know The Risks Of Excessive Leverage

While i do appreciate a small amount of leverage in Forex trading, i feel that traders should not be tempted by the high degree of leverage offered by some brokers. it is not uncommon for brokers

to offer 100, or 200 or even 400 times leverage to their customers in a bid to attract the largest amount of customers. do not choose a broker simply based on the highest leverage allowed or the tightest spreads or the lowest margin required.

With a smaller amount of leverage used on each trade, you can afford to give your trade more breathing space by setting a wider but reasonable stop. A highly leveraged trade can quickly deplete your trading account if it turns out to be against you as you would be trading more lots, hence racking up larger amounts of dollar losses. Also, if you employ higher leverage on a trade, but still want to risk not more than your pre-determined certain percentage of your trading capital, your stops must be tighter than usual in order to compensate the risk of trading more lots. Then again, having unreasonably tight stops is suicidal to your trade as you are not giving the currency pair much moving room.

Keep in mind that leverage is totally flexible and customizable to each trader’s needs. Having an aim of trading profitably is not about making your millions by the end of this month or even this year. The means of using high leverage is there; it is just as easily available to you as credit cards are. The thing is, the mere availability of these “perks” should not mean that you should take full advantage of it. Make smart trading decisions by considering the worst-case scenario. if you are not careful, you could end up like the majority – broke and scarred.

Grace Cheng


FX STRATEGY

The first verse of a rather inspirational and oft quoted Kipling Poem and somewhat apt in the current market. At the time of writing this we have been hearing details of a second wave of bank bailouts, Many of the banks have just informed us of further losses based on record write downs and so their share prices reflect a rather distrustful mood by sentiment. The pound has hit a 23 year low against the Usd, Jim rogers the well known investor has suggested that the UK is dead in the water, as is the pound,, urging those who follow him to sell any GBP, and of course President Elect obama is now no longer ‘elect’ but the president.

Well that was certainly going be the theme of my first piece for this the inaugural edition of FX trader magazine and i suspect you would agree that there is plenty of meat on the bone for any budding columnist. but with cable back up around 1.4300 at the time of writing and both soros and rogers claiming we have now

seen the bottom of the cable slide, the Banks shares now without any direction and with the feeling that the FsA here in the UK seems not too displeased that some funds have now lost money on their shorting of the banks, the FX market as whole seems a rather sane place to be, but hindsight is indeed a most precious commodity.

so it is with this rather mixed and muddled picture in mind that i remember the rudyard Kipling poem ‘iF’ and in particular the first verse

above. indeed we could consider the poem in an ironic sense, it is said that this poem was in fact written with regard to a failed 500 man raid instigated by the reform Movement and led by a certain Leander starr Jameson on the Boers in southern

Africa, which is now widely believed to have started the Boer war. ( Jameson was later tried and imprisoned in Holloway for his part in the mercenary act) We only have to look at the current climate and the few that led their institutions into a blind and almost dogmatic raid on all things pertaining to credit to apply this same analogy, but possibly in its more literal sense the verse highlights that FX is just the product that will allow you to keep your head, whilst others lose theirs.

over the course of the next few editions

of FX trader Magazine i shall attempt to disseminate as to why FX is indeed a product that may buck the trend of otherwise ‘dysfunctioning’ markets and look at how recent events may shape the FX market and all those that participate in it., but more importantly how

“If you can keep your head when all about youAre losing theirs and blaming it on you,If you can trust yourself when all men doubt you,But make allowance for their doubting too”

iF...

Rudyard Kipling

“why is FX a product that may buck the trend of otherwise ‘disfunctioning’ markets”

FXMARKET WATCH


some of those that participate in it may actually shape the market itself.

this was borne out of a conversation i had recently with a gentleman at a

social event, a very convivial social event i might add and an event not connected with my work in the city which invariably allows one a certain freedom of speech that in the confines of my environment is often held back As it turned out this chap held a rather enviable or some may argue unenviable position in charge of a large slice of real money for a rather large UK insurer and it was impressed upon him by his management the need for an alternative approach to investment, notably FX funds. now this was an interesting declaration on two levels, this particular company is one of those that could be considered to be typical of a traditional UK financial institution in those eyes that

would stereotype it as such, including myself. it could be argued that it has a monotone approach to financial services and dare i say a certain type of bland Britishness. With this in mind and during the present climate, firstly, why would said institution decide to veer from its traditional rather safe course and secondly, where risk is the word on every bodies lips, why would an institution such as this look to a product that has long been considered leveraged and risky. Further on in the conversation was probably the very reason that many similar managers have only very recently chosen to look at FX as a product and are now raising these issues. For a while now we have all heard of the Asset class nature afforded to FX and for as long now we have heard the buzzword ‘Alpha’ when considering FX as an investment, but very simply and continuing throughout the conversation the gentleman could not understand how anyone could

predict the movement of currencies. it is a very valid and perfectly reasonable question but here is perhaps the problem in a nutshell and on further investigation we may all find out that us as participants in the FX Market are equally to blame for the fact that a large percentage of money held by those large institutions, whether in pension or as an investment vehicle in its own right, choose to apply funds to traditional investments and why FX, as an investment option only rears its head in times where those traditional investments are not performing.

i suspect the question i am asking is how FX can become a natural choice of non correlated investment for the potential investor and how the providers of such fit in to the changing market place in both FX as an investment and FX in its traditional sense. Whilst there are many avenues of inquiry and there is indeed much to dissect, in this first edition lets address the question raised above.

How can anyone predict the movement of currencies?

Unfortunately it was not the sort of evening where one could start waxing lyrical about the fact that this was perhaps the wrong question to be asking, but let us understand the primary driver of any currency fund worth its salt,…..risk. it is very easy to enter a position but the talent lies in managing the risk that is inherited from taking that position and as importantly the fact that risk determines the point of entry in most cases. An industry colleague told me that while sitting in front of potential investors to his currency fund, it Coctail Party – Alex Katz

content * content * contentFX MARKET WATCH


FXMARKET WATCH


became apparent to him that the simplicity of the model he employed was lost on seasoned analytical minds from an equity background. to them the argument was that there are fundamentals in the equity markets that one addresses, corporate earnings and therefore dividend yields, which of course directly or indirectly provide two separate investment streams, capital growth and income. Yes the wider markets and public are now accustomed to the demonised hedge fund that sells short the stock and is subsequently blamed most of the time for share prices moving against what are the true fundamentals, but the idea that something as intangible as selling one currency for another or for that matter buying could be working under similar quantative logic as say a long short equity fund, seemed utterly incomprehensible. to then take it a step further and suggest that perhaps the currency markets are somewhat more robust due to the greater and some would argue infinite liquidity seemed to only blur the judgement further.

At the risk of suggesting i spend my every waking moment in the company of FX or currency fund managers, another market colleague of mine highlighted this issue on liquidity further, where he aligned his own currency fund to that of a speed boat in comparison to maybe a large traditional equity fund or money market fund that he suggested as an oil tanker. in the first instance the speed boat can nimbly navigate its way through calmer seas than that of the oil tanker, but should the seas become so choppy that a new course is required the speed boat can act equally as nimbly, re-calibrate

its course and take action as necessary, whilst the captain of the tanker is still trying to reach the bridge. it is obvious that any small fund is easier to turn around than any big fund, but in the case of FX unlike many traditional financial product funds, the liquidity of the market is such that there will arguably always be a price. obviously scalability is an issue, we all know that there is a critical mass to any fund in terms of its performance in regard to assets under management and FX is

no different, but the point i suspect my colleague was making is the natural depth of liquidity, (let’s not forget that aside from generating ‘Alpha’ the FX market is essentially a requisite for any cross border business). Consequently the liquidity and price risks that are inherent in other financial product funds are mitigated greatly by the FX markets unique depth.

in order to address this even further, fund of funds that are ubiquitous in

more traditional financial markets also exist in the FX Market, the overriding memory of the conversation with the well known insurer was the misunderstanding that a currency only FX fund is the same as the next, you simply take a view on whether the currency goes up or down, which in simplistic terms is of course correct, but like those traditional financial product funds there are many ways to skin a cat. intraday, high frequency, quantative, discretionary, longer term, carry, arbitrage are some of the titles applied to different models, some apply a number of characteristics in order to delineate and un-correlate even further, but perhaps i am getting a little too technical for myself here The fact is that much like traditional products there are different methodologies in creating ‘alpha’. And much like a fund of fund manager so there are multi manager funds in the FX market. This was somewhat of a revelation for a person who in their own admission,

had not really paid much attention to FX .

so what about volatility? one may

argue that this is only the friend of the Broker-dealer or liquidity provider and of course it is, but on anecdotal evidence many of the currency only funds have mentioned that during the last 12-18 months they have been spoilt, and again whilst not scientific or in anyway proven statistics, they (in my environment) have posted some of

“one may argue that volatility is really only the friend of the broker-dealer or liquidity provider”

the best yearly performance in their history, again like anything there are good and bad, but as we mentioned before any fund worth its salt addresses risk and in these markets that same logic whether employed discretionally or quantatively, one might argue, is far more robust in its application than, say, a traditional financial market product that has been one sided in its movement in recent history.

the ‘return of volatility’ as it has been labelled by a colleague reminds me of a conversation i had with one of the few FX only funds that existed in the hallowed streets of Mayfair many moons ago, who on the inception of the EUr, his discretionary fund, he suggested, had less chance of improving yearly

performance, as it was argued that at the time of the conversation, there were then only maybe 6 real moves in the majors during the year. if we look at the benchmark 3 month historical volatility in say EUr/Usd today, it has increased considerably. After september 2008 and the real shocks of banks collapsing it rose from just over 10% to 24% in the proceeding quarter, and the other majors produced similar notable increases.

so evidently there is truth in the volatility argument, and the fact that perhaps no one could actually predict the movement of currencies, perhaps the idea of funds that are leveraged also increases that insecurity further, but perhaps we as participants in the FX markets are simply

fulfilling our own prophecies of being the less glamorous asset class. Perhaps we unconsciously cultivate the myth that we work in a market that is the domain of a certain breed of character. or perhaps we actually work within a market that in the present climate needs a re-branding , unlike exchange traded products we have no central face that will do this for us, an otC market is naturally fractured in its message and therefore its service, Perhaps all of ‘us’ Broker dealers and Liquidity providers need to work together more closely.. After all as a product in its own right there is none that is more transparent in its mechanics or less credit intensive than a simple spot foreign exchange deal. Maybe it is not necessarily the product that is the problem but the lack of transparency in the market itself and again the fractured nature of it but as they say, this is another conversation. so perhaps it is time that the FX market grew up a little, which leaves me reciting the final 2 lines of that same rudyard Kipling Poem:

“Yours is the Earth and everything that’s in it, And - which is more - you’ll be a Man my son!”

Ben Brown

- Next edition – Ben will be looking at the role of the Liquidity providers and the Broker Dealer.

FX MARKET WATCH


The popularity of options since the turn of the Millennium has been nothing short of impressive. Foreign Exchange is the largest, most liquid market globally. According to the Bank of international settlements, over 3 trillion Usd of volume is transacted daily. And estimates suggest the options market generates about 300 Billion Usd per day. As this market has quickly matured, there have been some marked i n n o v a t i o n s and efficiencies with products, liquidity, price transparency and execution platforms. With the credit crisis related volatility, more and more corporations and investors are using options as a much safer and responsible means of hedging/speculating. With each passing day, participation in Foreign Exchange options, has moved from choice to necessity.

options are derivative instruments whose values are derived from underlying interests or assets. simplistically, options provide the buyer the right –not obligation- to buy or sell said underlying interests. For instance, when the purchaser buys a call contract on the Euro dollar, it entitles him to buy Euros and sell Us dollars in the spot market at a predetermined

price and maturity. Equally, the put purchase allows the buyer of the option the right to sell Euros against Us

dollars at a set strike price and maturity. Quid pro quo, of course. A premium is exchanged for this right. The calculation of premium is determined by various input factors as well as other market conditions which shall be discussed in subsequent articles. This is merely intended as a rudimentary, yet colorful, primer on options.

FX oPtionsPriMEr

content * content * content FXoptions

More and more investors are using options as a much safer and responsible means of hedging/speculating


Apart from the payment of premium, there is very little downside to using options. These premiums are expressed as a small percentage of notional, allowing for significant leverage in the market. in a world where capital has become increasingly scarce, options are clearly the sensible solution. sellers of options with deliverables are able to monetize much of their FX exposures by applying premiums earned to gains/losses of their positions. The otC (over the Counter) market allows buyers and sellers to custom tailor each contract to their preference: currency pair, notional, maturity and strike price.

For speculators in volatile markets, options eliminate the potential of being stopped out on positions. The slippage on spot stop losses can be very costly. Consequently, it is no wonder that the largest institutional clients of FX option desks tend to be their spot traders. That says a lot. in many instances, market views are sound and correct. That being said, however, market noise and illiquidity are often what trigger stops. When both hedgers and speculators avoid the disruption and pain of costly stops they are able to focus on their core business/trading strategies.

The following depicts the simple profit-loss characteristics in both puts and calls. The Vertical axis represents PnL and the Horizontal represents underlying asset price.

As can be seen below, when buying an option, the profit potential is unlimited whereas the potential loss is limited to

the amount paid for the premium. selling an option gives you a premium up front, but the premium is also the maximum profit you can take. so, if you sell an option, the profit/loss scenario is the opposite of when buying one. (Limited gain, unlimited loss potential).

in the vanilla options world, structures and strategies involve calls, puts or a combination of

both. The following depicts some simple vanilla structures which are used quite frequently. Each strategy can be tailored to suit views, risk tolerance, budget and overall objectives.

For speculators in volatile markets, options eliminate the potential of being stopped out on positions

content * content * contentFX options


FXoptions


Objective Simple depreciation

SimPle lOng Put: Sentiment BeARiShObjective Simple appreciation

SimPle lOng CAll: Sentiment BulliSh

Objective: Capitalize on an aggressive breach of either strike

lOng StRAngle: COmBinAtiOn lOng CAll/lOng Put CAll/ShORt Put: Sentiment nOn DiReCtiOnAl BiAS BReAKOut

Objective Collecting premium anticipating a move lower in spot

SimPle ShORt CAll: Sentiment BeARiSh

Objective earning premium anticipating a move higher in spot

SimPle ShORt Put: Sentiment BulliSh

Objective: Collect premium while betting the spot price remains contained in a range between two strikes

ShORt StRAngle:COmBinAtiOn ShORt:Sentiment RAngeBOunD BiAS

As mentioned earlier, the depth and maturity of this market have brought significant enhancements. Exotic options, which shall be discussed in the near future, have allowed for more cutting edge risk management and speculative strategies. From a liquidity perspective, electronic platforms now provide impressive access, transparency and execution into the home offices of millions of retail traders.

the FX options market has enjoyed a robust annual growth rate of 20%. options are here to stay and are clearly the way of the future.

Ashif F. Jiwani

In the next articles, the author will cover the pricing dynamic of options; the reasons and suitability of hedging ; speculative trading and basic options strategies ; Black Swans and exotic options.

FX options


Objective Capitalize on an aggressive breach of betting the spot price either strike

CAll SPReAD:COmBinAtiOn lOng CAll/ShORt CAll:Sentiment mODeRAte BulliSh APPReCiAtiOn

Objective Capitalize on limited depreciation with low net premium costs

Put SPReAD:COmBinAtiOn lOng Put/ShORt Put:Sentiment mODeRAte BeARiSh DePReCiAtiOn

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C31614 FX Trader Mag 274x216 31/3/09 11:58 Page 1

http://www.saxo-online.com/forex?77tadunit=997fbfcb&77tentry=fxtradermag

STRATEGYFX


in technical analysis, there are 2 main types of indicators: trend indicators – also defined as “lagging” indicators - and oscillators – also defined as “leading” indicators.

in the first category we find for example moving averages or MACd. these can be very useful when prices register strong oscillations, forming strong trends. However they don’t give us any indication about the starting point of a trend. they simply identify it in an attempt to follow its full development.

this first type of indicator generates buying or selling signals only when a trend has already started to develop, and can be considered as “late” because they don’t spot the beginning of the move. this said, generally they also generate safer trading decisions, precisely because they follow an existing underlying market direction. this is why trend indicators give better results with strong price movements.

in the second category of leading indicators, we can find for example oscillators such as rsi and stochastic. the way they work is that they try to identify overbought and oversold situations in order to anticipate the trend inversion, or the beginning of a new price direction. in that case, the indicator will give better results during a trading range, as buy and sell signals will generate trading decisions, which are linked to the anticipation of market moves.

that’s why it is fundamental to understand in which kind of market we’re operating. during strong trend periods, it will be preferable to use lagging indicators, whereas, during a trading range, it will be wiser to use leading indicators. Most of the time, using leading indicators during strong trend periods, or vice versa, using oscillators during a trading range, will generate more loss than profit.

Using the crossing point between

the price and the moving average as a buy or sell signal during a trading range, could give false signals which would generate a series of stop losses. in the same way, oscillators used during strong market movements will often read overbought and oversold conditions as trend inversions, which won’t be confirmed and therefore will generate large losses, if positions aren’t protected by the right stop loss.

Becoming familiar with one or other of these categories of indicators is a matter of personal choice. Many traders use both kinds successfully. But, in any case, it is important to recognize which market phase we are in. A mystic skill is then to be able to predict the following market phase or trend.

in this article we would like to introduce a different methodology, which is to use oscillators as trend indicators. this technique combinethe best qualities of both types of indicator.

UsinG osCiLLAtors As trEnd FoLLoWinG indiCAtors

We’ve chosen to use one of the most famous technical analysis oscillators: the stochastic indicator. (But the same principle can be used, with the necessary adjustments, for all kinds of oscillators).

the stochastic gives precise indications regarding overbought and oversold levels. on a 1-to-100 scale, the indicator identifies 2 zones: when the indicator reaches the level of 80, we are in an overbought situation and therefore prices are then expected to go down. on the contrary, when the indicator reaches 20, we are in an oversold phase and prices are then expected to go up. in a trading range, such signals

will be very useful to read price movements, whereas they won’t be of use in a period of strong bullish or bearish trend. to use the stochastic indicator profitably in a trend phase, it is necessary to check when the K% line is above 80 and remains above this level. then it is possible to anticipate the beginning of a strong bullish trend. And this trend will be confirmed as long as the K% line doesn’t return back under the 80 level. the same technique can be implemented in the reverse situation, when the K% line is and remains below 20 and anticipates a bearish move.

this methodolog y allows us to distinguish between the various

market phases: when the indicator will move in-between 20 and 80, it will mean that the market is in a trading range. And when these levels will be broken on a stable basis, the indicator will identify a bullish trend above 80 and a bearish trend below 20.it will then be difficult – if not impossible - to forecast a new market direction if, for example, the 80 level gets broken. With a bit of experience, being able to recognize when the trend is in a potential inversion state, will be very useful. Here are a few examples of the implementation of this technique.

on chart n.1 the K% blue line, reaches values below 20 on 30 July 2008. see how the indicator remains oversold (with values below 20) for 44 days in a row, and then returns back above 20 on 13 september. After a bullish correction, the K% line returns back to an oversold condition, and from october 3 stays in this condition until october 30. during the first bearish move, the stochastic succeeded in following the trend for 1,770 pips. in the second bearish trend, the oscillator confirmed the move for 854 pips.

it is important to note that the bullish correction which links these 2 phases, reaches its maximum level precisely when the stochastic reaches 80 (overbought). As explained before, this is exactly what can help anticipating the beginning of a bearish trend.

CHART 1: EUR-USD DAILY K% 34 Smoothing 3 FROM 07/30 CLOSE 1.5589 TO 9/13 CLOSE 1.3819 PIPS 1770 44 DAYS FROM 10/03 CLOSE 1.3819 TO 10/30 CLOSE 1.2965 PIPS 854 27 DAYS


STRATEGY FX

in this example showing the Usd-JPY hourly chart (chart n.2 ), the K% line remains in an overbought situation for 41 consecutive hours, confirming a bullish move of 215 pips.

Here is another example (chart n.3) of 2 bullish trends where the K% line remains in an overbought condition for 41 hours and then 24 hours. The correction phase between these 2 bullish trends is very short and the oscillator doesn’t succeed in canceling the overbought conditions. As soon as the K% line returns above 80, the trend gains new momentum during 180 Pips.

on daily timescales, this technique works particularly well between 13 and 18, whereas with short timescales values between 30 and 38 give very good results, and the value 34, which is also one of the Fibonacci sequential numbers, seems to work very well with many currency crosses.This methodology, like all trading techniques, can be modified to be adapted to each trader’s style and preferences.

to conclude, let’s emphasize the fact that combining the interpretation of a market trend with the use of an oscillator can be very useful. Using the stochastic indicator: when the K% line fluctuates between 20 and 80 the indicator confirms a trading range and it is possible to sell at 80 and Buy at 20. When, on the contrary, the overbought and oversold levels (80 and 20) are broken on a stable basis, the oscillator helps identifying the new market phase, and we should change strategy: Buy above 80 and sell below 20.

CHART 2: USD-JPY HOURLYK% 34 Smoothing 3FROM 3/20 17.00 CLOSE 95.60.56 TO 3/24 19.00 CLOSE 97.85 PIPS 215

CHART 3: GBP-JPY HOURLYK% 34 Smoothing 3FROM 3/20 12.00 CLOSE 137.56 TO 3/23 19.00 CLOSE 140.44 PIPS 288FROM 3/23 22.00 CLOSE 141.52 TO 3/24 22.00 CLOSE 143.32 PIPS 180

STRATEGYFX


A Perpetual Quest

there has been a perpetual quest by traders, to identify quantifiable trading patterns,

ever since ‘candlestick’ charts were developed, on the world’s first trading floor; the dojima rice Exchange,

founded in osaka, Japan, in 1697.

The advent of computers has made that quest considerably easier, but one factor has remained constant; markets are still traded by people. As long as that remains the case, they will always be driven by only two factors, namely

fear and greed. There have been many observations made about the predictability of crowd behaviour, but perhaps the most famous and often quoted is that of the famous German poet, and philosopher, Friedrich von schiller who said,

‘Anyone taken as an individual is tolerably sensible and reasonable - as a member of a crowd, he at once becomes a blockhead.’

The Holy Grail

However, although there is certainly non-random behaviour in the financial markets, equally there is almost certainly no ‘Holy Grail’ or ‘secret formula’, that even the most successful quantitative funds have discovered. if that were the case, there would be no need for them to trade so many instruments, over so many time frames, with many different models, and to focus so much of their resources on efficient execution (which will be covered in a later article).After many failed attempts, when the author finally began to post some very consistent returns, over a two year period, a good friend inquired what his secret was and what he had discovered. He replied that he hadn’t found any secret to the markets, discovered anything new, nor stumbled upon any ‘Holy Grail’. He had just identified a few small, robust, edges, which were traded across as many crosses as possible, to which the very astute response came, ‘That is the Holy Grail’.

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Building robust FX trading systems


Understanding the Odds

A casino only has a small edge on any given spin of the roulette wheel and will lose many times in a night, and indeed many times in a row, but statistically, it will win overall, over time:

e.g. A roulette wheel typically has 38 slots with 2 zeros. This gives the house an edge of 2/38 x 100 = 5.26%, when players bet on red or black. Even such a relatively small edge produces a substantial and incredibly consistent revenue stream for the casinos and their shareholders. The more times the wheel is spun and the more bets are made, the more the casinos probability of winning tends to 100%.

This is exactly what the systematic trader should be seeking to achieve – identifying and exploiting a small edge, as many times as possible; being the casino. Therefore, the first step in developing a robust system has to be identifying an edge. to do this, the

main tools of any system developer are good historical data and software with which to analyse it. There are a number of excellent sources of data and software, readily available now. This is a huge advantage, compared to even relatively recent years, when it was very hard to come by, particularly for foreign exchange data, with no central exchange, the dominance of voice brokers and a very fragmented market. The rapid increase in computing processor speed is also a huge advantage.

once we have those tools in place, the next task is to quantify trading ideas and this is where any system developer will soon be able to relate to the famous Thomas Edison, inventor of the light bulb, who famously said,

‘I would construct a theory and work on its lines until I found it was untenable. Then it would be discarded at once and another theory evolved. This was the

only possible way for me to work out the problem... I speak without exaggeration when I say that I have constructed 3,000 different theories in connection with the electric light, each one of them reasonable and apparently likely to be true. Yet only in two cases did my experiments prove the truth of my theory.’

Successful Trading Systems Unlike Edison, we have the advantage of knowing that profitable trading systems can be developed, as there are a number of proven systems already in existence, which one can easily test, such as the ‘Channel Break out’ (CBo) system, made famous by the ‘turtle Experiment’, where richard dennis and William Eckhardt had a wager about whether successful trading could be taught (and proved that it could). Those same channel break out/trend following, techniques have been exploited by many successful funds. The ‘opening range Break

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out’ (orB) is another system, which has been proven to have a consistent edge, perhaps most famously exploited by toby Crabel.

the reason that these systems have proven to be robust is almost certainly because there is a sound rationale behind why they work. the CBo system relies on the fact that markets trend. it has been shown that they often have larger trends than would be expected in a ‘random walk’ or ‘normal distribution’, often displaying ‘fat tails’; examples of which are almost countless, with many ‘Black swan’ events happening as recently as last year.

the orB system has worked well in the futures markets, as they have a fixed open, from which to define an opening range, and all futures markets display similar volume characteristics; as illustrated by the following sample of s&P volume on the CME, taken over several months in 2008 (Local Exchange time). this has remained constant over time and is something that the legendary Monroe trout also observed. in Jack schwager’s book, ‘the new Market Wizards’, first published in 1992, he is quoted, as saying,

‘The most liquid period is the opening. Liquidity starts falling off pretty quickly after the opening. The second most liquid time of day is the close. Trading volume forms a U-shaped curve throughout the day… Generally speaking, this pattern holds in almost every market. It’s actually pretty amazing.’

Foreign Exchange vs. Futures Markets

However, to develop robust FX trading systems, we have to take into account that FX behaves differently to a typical futures market, and unfortunately there is no fixed open or close; Asia is already trading as Europe comes in, followed by London. similarly with the ‘closes’; new York and Chicago are still trading, while London and Europe are going home.

This is probably why it is considered more challenging to build successful FX trading systems: The opens and closes of futures markets are not random events and have distinct, non-random characteristics.However, the FX markets have their own non-random behaviour. it’s generally accepted among traders that each currency cross is different, with each having its own particular nuances.

to some extent, this is true, and therefore, if one finds that a certain set of parameters work well for EUrUsd but not for GBPJPY, then it’s easy to find arguments to explain why the two crosses may behave differently, with economic data and news events being reported in different time zones etc.

There are also moves specific to certain currency pairs, as FX is involved in every cross-border transaction across the world. As a spot trader, i recall

a certain, oil oriented, corporate customer always selling a market-moving amount of GBPnoK at a specific time every Friday.Historic price data analysis may well have revealed that non-random behaviour, but without knowing why it occurred, it would have been foolish to trade it, as one may have lost a huge amount of money if the corporate customer changed its trading habits.


FXTRADING SYSTEMS

There are also much broader characteristics of the FX markets. it is very well known that Europe is the largest trading centre by volume, followed by the Us, with a very illiquid trading period, as the sun crosses the Pacific, until Asia comes in.

Although genuine FX volume data is impossible to quantify exactly, being so fragmented, and with no central exchange, we can use the CME currency futures as a proxy. We find that their volume distribution is very different to the distribution of a typical futures market, as discussed above. The chart above shows a similar average hourly volume for the Canadian dollar Futures contract, over a three-month trading period (UK time).

Just as with the futures markets, although volume analysis may not produce a robust trading system, it does illustrate that FX clearly isn’t entirely random and there is a very predictable, robust pattern, repeated by traders every day.

Fool’s Gold

With all of that in mind, it’s relatively easy to find systems that work well for specific instruments, on historic data, which would appear to have huge ‘edges’ and to come up with explanations as to why those parameters would work for a certain cross.

When testing enough parameters though, one will always find parameters that work for any indicator on a given market. take, for example, just testing a simple two moving average crossover combination, between 1 and 50. This will return 2,450 different equity curves (assuming we count the 10 event crossing above the 20 event moving average, as a buy, and vice versa for a counter trend trade).

By pure statistical probability, a large number of those combinations will be profitable, and statistically some of those will also be profitable ‘out of sample’. in fact, it is a statistical certainty that, if you look at enough parameters, some of them will test

well, both ‘in’ and ‘out of sample’. However, without any rationale, the resulting systems would not be reliable trading systems, being solely a product of statistical probability.

therefore, one has to be very careful and appreciate that just because a system works in simulations, it does not mean that one has discovered a robust, or even remotely reliable, trading system - another one of the countless errors the author has paid an expensive price to learn.

it is better to identify even just a small, quantifiable, edge that you understand and which has a sound rationale. to quote Monroe trout again,

Make sure you have an edge. Know what your edge is... Basically, when you get down to it, to make money, you need to have an edge and employ good money management.’

The Edge Effect

An often-used ratio for quantifying whether a system is ‘good’ is ‘Profit Factor’ (PF), being the gross profit divided by the gross loss i.e. if the sum of all the profitable trades for a system, over a given period, was $1.1 mio, and the gross losses of all the losing trades was $1.0 mio, the Profit Factor would be 1.1/1 = 1.10

to put this in perspective, to use the roulette analogy: if a player bet on red each time, the player would win on average, 18 out of 38 spins of a wheel (with a double zero table). the house



would win 20 times out of 38 (i.e. every non-red slot). For illustrative purposes, let us assume the payout is equal to the odds. This gives the house a PF of 20/18 = 1.111

With a single zero table, the house PF is just 1.055 (19/18).

The important point is that the house edge is a very small one, though still incredibly profitable. Looked at a different way, the odds of the house winning on any single spin of the wheel are only slightly better than evens, being 20/38x100 = 52.63% for a double zero table and 51.35% (19/37x100) for a single zero table.

Even with only that slight edge, as Albert Einstein said,

‘No one can possibly win at roulette, unless he steals money from the table, when the dealer isn’t looking.’

trading is no different. All a trader has to do, to be consistently profitable, is to identify an

edge, and apply good money management. Unfortunately, that is much easier said than done. Just as the casino’s edge is in knowing certain facts, a truly robust trading system, can only be built on known, quantifiable, non-random, market behaviour.

if a trading system enters a losing streak, a statistical certainty that it (often) will, it is then possible to identify whether it is just an expected statistical ‘run’, or whether something has changed fundamentally in market behaviour. A casino knows that each of its tables will have many losing ‘runs’ and it also knows that is a statistical certainty. this is where money management plays a vital role. Without understanding its edge, and without being able to quantify it, a casino would not be able to operate.

As we have seen, with an arbitrary trading system and an arbitrary set of parameters, no matter how good the ‘in’ and ‘out of sample’ results are, a system is very unlikely to be robust. Equally importantly, it would be impossible to know if the system had degraded, without understanding the underlying reason why it worked.

Caspar Marney

All of the topics touched on here will be addressed in more detail in Caspar Marney’s following articles.


FXTRADING SYSTEMS

GLossArY

Base Currency: For foreign exchange trading, currencies are quoted in terms of a currency pair. The first currency in the pair is the base currency. For example, in a Usd/JPY currency pair, the Us dollar is the base currency. Also may be referred to as the primary currency.

Cross-rate: The exchange rate between two currencies where neither of the currencies are the Us dollar.

Currency pair: The two currencies that make up a foreign exchange rate. For example, Usd/YEn is a currency pair.

Forward transaction: A true forward transaction is an agreement that expects actual delivery of and full payment for the currency to occur on a future date. This term may also be used to refer to transactions that the parties expect to offset at some time in the future, but these transactions are not true forward transactions and are governed by the federal Commodity Exchange Act.

Leverage: The ability to control large dollar amount of a commodity with a comparatively small amount of capital Also known as ‘gearing.’

Quote currency: The second currency in a currency pair is referred to as the quote currency. For example, in a Usd/JPY currency pair, the Japanese yen is the quote currency. Also referred to as the secondary currency or the counter currency.

Security deposit: The amount of money needed to open or maintain a position. Also known as ‘margin.’

JW.: How long have you traded foreign exchange and what first attracted you to this industry? tell us about your career evolution

r.M.: i executed my first trade while i was still in college in the late 80’s in the dollar yen and i knew this industry was for me. i started reading everything i could get my hands on and came to understand the industry both from a trading and research perspective. All in all, i have been trading FX for over 22 years and founded richmond Group in 2001. Prior to 2001, i traded proprietary capital for a nYsE member firm, several private institutional investors (futures and FX), and also for my own company, richmond Commodities Corporation.

JW.: What do you particularly like about your job?

rM.: The competition! The challenge. Each day is different.

JW.: is FX a unique market? in what trading currencies is different than trading other financial instruments?

rM.: Absolutely, sovereign currencies are effectively a direct proxy of the financial health and stability of a country (relative to other countries). it is arguably the most liquid asset

class out there as all other asset classes are priced in a sovereign currency. if one wishes to invest in a particular view or idea in a country, one must go through the currency first to express that view. For example, if one is bullish Asian tech stocks and that will be the latest “macro” play then it will be expressed through the money flows through that particular currency first. i believe a currency play is the most liquid way to invest in emerging markets and arguably the easiest to liquidate when the need arises.

JW.: When was richmond Group born? What ideas brought to its creation?

rM.: i launched richmond Group Fund Co. in 2001 after spending a good portion of my career assessing the strengths and weaknesses of both fundamental traders and systematic (quantitative) traders. As a fundamental trader, i felt like i could always out trade a model. What i learned throughout my career is that although perhaps one can out trade a model, is that it is incredibly difficult to do this over an extended time period across more than a few specific markets. The allure of the quantitative process is that a system can process a much broader array of markets. i embrace an approach that brings discipline and

consistency to risk management and trading/investing ideas..

JW.: How are you structured in terms of headcount and offices/geographic distribution?

rM.: our office, process and capabilities are streamlined and efficient. This is due to efficiencies in computing power and access to data. our headquarters / primary office is located in richmond, Virginia. We have several backup locations on different power grids (including a generator backup with a two month supply of fuel). From a headcount perspective we have a staff of 10 professionals .in addition, we are assessing the possibility of opening an office offshore as well.

JW.: What are the key positions in an FX Management company?

rM.: For us specifically, key positions include trading, research, risk management, operations and marketing.

JW.: Are you a regulated company and do you keep and update procedure manuals, and a compliance and risk management policy? How time consuming, and how important, it is to satisfy regulation requirements on one side and internal procedures on the other?

robert Marcellus

founder and president of Richmond Group Fund, Virginia-US based alternative investment management firm

tells how he reached a +18,48% performance in 2008

INTERVIEW

FX FX MANAGERS

Manager Richmond Group Fund Co., Ltd.Strategy Global Currency ProgramLocation Richmond, Virginia, USAAssets Under Management 65 mln UsdType 100% Systematic QuantitativeStyle A mix of trend following, carry and mean reverting styleInstruments FX Spot or NDFCurrencies 30 currency pairs from majors to emerging markets


interview by JW Partners for FX trader Magazine


rM.: We are regulated by the national Futures Association (nFA) and Commodity Futures trading Commission (CFtC) in the Us. our offshore funds have been regulated by the Bermuda Monetary Authority as well as the Cayman Authorities. We keep all of our various manuals up to date, ranging from trading and compliance to risk management and disaster recovery manuals. We are subject to both regular and “on the spot” audits. The largest time commitment is the initial process of putting together any of these manuals with regard to putting down the detail of what we do every day into writing.. The maintenance process is minimal by comparison. The important aspect of such process is that it helps a firm and its staff to align effective internal procedures with external requirements. it makes us more efficient. regulations are typically in place for a very good reason and in other words the procedure of putting together a well thought out manual, strengthens the internal process itself. As an example the disaster recovery manual was unexpectedly used and the process successfully put to the test early in life of the company and later profiled by the MFA (Managed Futures Association) in october 2003. We were also noted by the securities Exchange Commission in the Us at a regulatory conference as having one of the better protocols in the Us institutional advisor markets.

JW.:You are in charge of the currency program. How would you describe your investment strategy?

rM.: We are a quantitatively based strategy that comprises pattern recognition concepts, short term volatility inputs and trend based components. our time horizon is of a short to intermediate nature with an average holding period in all sectors of approximately ten days and under, depending on the program target. The systems are designed to be uncorrelated to traditional equity and fixed income investing and slightly less correlated to traditional long term trend-following approaches and have no directional biases.

JW.: How and when did you develop your current FX management strategy?

rM.: i developed our core trading systems in the mid to late 1990’s. My goal was to develop a systematic process that emulated a discretionary trader, but to do so systematically. This was a process that evolved throughout my career as a

proprietary trader and culminated in the core models and concepts behind our FX strategies.

JW.: risk, an exciting yet dangerous word. How do you manage risk?

rM.: We have always been well-known for the strength of our risk management process ranging from operational risk and disaster recover to trading and execution risk. i think that most importantly in all aspects of risk, is that we look to understand and mitigate risk in real-time.

As an example, from a trading perspective specifically, we have a rigorous four-stage process in place. in the first stage, position size is controlled by risk and volatility. The second stage balances risk in each market and sector as a fixed percent of equity. The third stage is provided by the responsiveness of the actual system exit signal (“trailing stop”), which is dynamically updated daily. And the fourth stage involves the diversification of positions. A short-term look-back period in the risk overlay contributes significantly to its dynamic nature. risk management and diversification are a priority in the trading approach since it is our opinion that one will not know from which market the next major price trend will occur. our objective for the risk management system is to expose the portfolio to multiple potential market moves while keeping overall risk to a minimum.

new position risk is limited to approximately one quarter of one percent of the total account equity under management. This stop-loss level, however, cannot be guaranteed with absolute certainty due to the potential for extreme market movements and illiquidity but it does help mitigate exogenous event risk by keeping our leverage low compared to our peer group. Also, it is possible that the risk management component of the trading system may override the signals in very extreme and highly volatile market conditions thus removing a potential profitable trade from the portfolio. it is our opinion though, that this approach has served it well in the past and will continue do so in the future.

JW.: What’s an example of the kind of trade you might have used back in the years but would never repeat today, and what was the biggest value from this learning process?

rM.: our core trading models and systems have been in place since i launched richmond Group in 2001. over the years we have made

selective research enhancements. Having said this, our core trading models and systems are incredibly robust. if market conditions now were identical to 2001 and we were trading the same markets, then for the most part, we would execute the same trades.

JW.: do you use a blend of strategy types for diversification or one and only?

rM.: our process is a unique one. We do not rely on one model, nor do we use a blend of models simultaneously in the traditional sense of letting them all just net each other our. We utilize multiple systems in conjunction with a pattern recognition overlay. The pattern recognition process is a systematic/quantitative process that ascertains and defines the current trading conditions and matches it with the appropriate proprietary model.

JW.: How do you think has your performance been over time? What market conditions are expected to have a positive and negative impact on it?

rM.: We are pleased with our performance throughout the years. our Global Currency Program annual rate-of-return is +7.54% not including any interest and net after all fees. We were up +18.48% in 2008 and we do a great job of capturing directional opportunities when they are available.

With regard to market conditions, markets that have a positive impact on our performance are markets indicative of our current environment: trending markets, markets which become volatile quickly and then sustain the new trend with continued price movement. The ideal scenario for us is entering trades just as the “long-term” trend begins to appear and exiting trades rapidly during “counter-trend” periods. in addition, we typically have responsive trade “re-entries”.

Weak markets for us are choppy, range bound and decreasing volatility environments, but this is where the diversity of our 30 currency pairs and a lack of bias in the models really helps.

JW.: do you trade all the currencies in a similar manner?

rM.: Yes, we utilize the same core trading models and we trade all currency pairs in our portfolio in the same manner.

JW.: Can you give some recent examples of where you have made a unique winning decision?

rM.: sure, let’s show russian ruble analysis

FXFX MANAGERS

and trading. Macro environment: in the first half of 2008, russia enjoys revenues from multi-year surge in energy prices. They plan their budget accordingly with overly optimistic assumptions. russia’s financial problems were masked by revenue projections. in addition, the trend towards controlling the energy industry by the government accelerated, reversing the more free market stance that saw the ruble appreciate almost 40% against the Usd form 2003 to mid 2008. russia invades Georgia in summer of 08’. Global investing community loses confidence in the russian advances of 03’-08’. investing community realizes that russia’s inward turn towards controlling industries and hostility towards neighbors is for real. ruble collapses, along with oil prices, for the rest of 2008. russia loses over a third of its foreign currency reserves in 2008 in a 3 month period, trying to defend the capital flight.

Quantitative trading models for richmond pick up on momentum shift and volatility expansion in early August of 08. Momentum and volatility portions of the models “override” classic carry models and long term trend components to reposition the portfolio for potential “carry unwind”. richmond sells short ruble as Georgia

“crisis” develops due to technical signals. Balance of August 08’ saw trending components of richmond models confirm the carry unwind and capital flight out of the ruble. richmond multi model strategy subsequently maintains and adds to short ruble positions for the balance of 2008’. short ruble versus Usd turns in one of

the strongest performances in our portfolio of 30 currency pairs.

JW.: do you believe in the superior trend characteristics of less mature currencies, and do you plan to add them to your studies and trading? or do relative lack of liquidity and wider dealing spreads outweigh any potential gains from being able to capture more inefficiencies?

rM.: Yes, as a firm we have long believed that emerging markets have superior trend characteristics relative to G-10 currencies. our Global Currency Program reflects our belief in the directional opportunities available in emerging markets; we trade 30 currency pairs around the globe and are always assessing addition markets for the appropriate level of liquidity.

JW.: do you think some of the less mature currency pairs are viable for individual traders, who don’t have to worry as much about huge liquidity? Would you suggest him to trade them?

rM.:Given the right process and approach, emerging markets are available to both individual traders and larger institutional traders like richmond Group. The key is approaching the less mature currency markets with an appropriately healthy time frame and a process that is responsive to changes in liquidity.

JW.: When developing strategies how approximately would you expect to allocate your time among building entry signals, exit signals and money management rules?

rM.: For us the research and development of creating, building and implementing our trading models (these include entry and exit signals and

money management rules) can take as few as several weeks all the way to a multi-year process in order to get the right mix. We tend to be working on multiple and varying concepts at the same time. We assign some staff to specific research targets, markets, or risk models, and others have a general approach. some ideas have to sit on the

shelf for a long period of time for our confidence to build or to find the right ingredients.

if you actually break out the detail, we tend to spend the most time on risk management concepts, money management, and finding efficiencies in our systems. While no less important, entry and exit signals tend to be easier to identify due to the inherent robustness of their nature. We have found that solid risk management helps to take the pressure off of identifying the “perfect” entry or exit. We spend a lot of time asking the question, “in what market condition does this system or pattern work well in”. We then spend time programming our models to identify the better areas to deploy the various models.

JW.: How much time do you allocate to further research and development of existing or new trading strategies?

rM.: We have 10 people. of those 10 people, half focus on research, so we place a significant level of importance to ongoing research aimed at both the enhancement of existing strategies in addition to the development of new strategies. We also constantly ask the trading execution team what they see so we can research their ideas.

JW.: do you believe in ever-valid rules, or every strategy loses its accuracy sooner or later? Have you ever found strategies that come back into phase after a long time in negative?

rM.: A robust set of rules designed to perform well under certain market conditions will always perform well under those same market conditions. i have found that designing systems that can capture an outlier move to be less accurate but more efficient in the long run. These would identify and stay with directional and trend type movement more so than others. The philosophy of “market trend” would classify as an “ever-valid” concept to build models around. i would agree that specific parameters would come and go into and out of favor. There is a subtle yet important difference here in understanding why a model is successful or not in a particular time period. A robust model combined with patience and discipline is a great recipe for success.

JW.: do you agree that one way to react to the ever-changing market is to adjust parameters? do you already use changing parameters based on volatility measures or filters?

rM.: no, we do not chase parameters, so to speak. our focus from day one was to design a

USDRUR, daily bar chart. Green bars for long positions, red for short posi-tions, black when squared.


FX FX MANAGERS

robust set of trading systems and models intended to stand the test of time. in fact, we specifically designed our systems with a much greater parameter tolerance so as to avoid feeling the need to make constant adjustments. What i mean by this is that if you change an input parameter in a typical trading model by 10% or 15%, your trading results will generally degrade markedly. our goal was to design a process and set of trading models, such that if you change one of our inputs by 50% or even 100%, then you do not impact our trading results significantly. risk management and the overall market state is more important to our thinking.

JW.: do you favor any particular time frames in your strategies, or do you diversify across a range of them? What is your average trade duration, and how high the trading frequency?

rM.: We diversify across a range of short- to medium-term time frames. The average holding period in our Global Currency Program is 5-10 days. We find success in looking at time series relationships that do not always revolve around the daily reported prices in the newspapers.

JW.: What should an inexperienced trader watch when choosing the time frame to trade on?

rM.: Go as long term as possible so as to avoid multiplying and compounding your mistakes in a short period.

JW.: What are your average and maximum leverage used?

rM.: in the Global Currency Program we average leverage levels of 2:1 to 3:1 though the leverage employed in a particular market can vary widely. our few peak leverage spikes have been roughly 7:1. during 2008 our leverage ranged between 2:1 and 4:1 for the first three quarters before dynamically responding to the extreme market conditions and dropping to below 1:1 during the final quarter of the year.

JW.: How many execution brokers do you use? How do you split execution between electronic and “dear old voice”?

rM.: We are currently using 8 to 10 different executing brokers. We generally prefer voice in EM markets and electronic in developed.

JW.: What historical data do you use in developing your strategies? How important that is?

rM.: We used a massive and varied data set that goes well back before the 1920’s. The key to this

was that we did not just look at currencies. our goal was to look at the price behavior of financial instruments in general as far back as we could. This included equities, fixed income, commodities and currencies. Going back this far is critical to achieve an understanding of the data and markets.

JW.: What tools do you use in the strategy development process? A generic trading/strategy development platform, or special statistical/quantitative tools as well? Proprietary or third party softwares?

rM.: All of our internal research and risk platforms, were built internally and are customized and proprietary. We can use standard charting packages from vendors for the traders and some off of the shelf research and statistics packages but needed to develop our own to achieve the requisite trust factor.

JW.: How does liquidity impact the efficiency of your strategies? Have you already explored to what AUM limit the strategies would allow you to grow to?

rM.: Liquidity does not impact the efficiency of our trading strategies to a measurable degree until several billion under management. We expect our Global Currency Program could effectively manage $2-3 Billion. As long as we maintain a healthy time frame (longer for less liquid markets) for our trading ideas then we will manage just fine.

JW.: Many more investors are looking now at FX as an asset class, so one would anticipate seeing the volumes of your business continue to rise. Can you confirm this interest is already moving higher rapidly? For what reason investors should consider the FX Management sector right now?

rM.: We are certainly seeing an increased level of interest in all of our trading programs. We have seen a concerted shift in pension fund allocations to the space. i think that investors are looking at FX managed funds for a variety of reasons: performance, low correlations, daily liquidity, and as a method to reduce portfolio currency risk. Most of all, the FX space is the most liquid of all asset classes and the diversity (if you include EM markets) offers significant opportunity for directional price movement.

JW.: How would you describe the performance of FX managed funds compared to other asset classes and in particular to hedge

funds and equity over the past years?rM.: 2008 was a defining moment with FX

asset managers proving their worth. Hedge fund strategies vary so widely so it’s difficult to lump them altogether. But, we saw CtA (directional strategies) and Currency strategies outperform in periods of significant stress and hold their own during the quiet times. i am not sure what else you could ask for from a lowly correlated strategy in a liquid asset class.

JW.: This outperformance tends to occur during time periods when equities collapse as did a large number of long short and exotic hedge fund strategies.

rM.:What is the single biggest strength of your team? is there any particular advance that has taken place since richmond Group started that has particularly benefited your trading?

JW.: discipline and experience. our 3 person trading team has a combined 50+ years of market trading experience across a wide range of markets. They have navigated multiple risk events in both emerging and developed markets.

rM.: We keep working hard in improving our view on risk. risk related to both market environment and exploiting efficiencies in our own models.

JW.: At JW we say it’s more important to plan and know how to react than forecast, but come on, give us your feeling about currencies over the next months? What’s your 6/12 mths forecast for the most popular, EurUsd.

rM.: The bias for 09 will be risk aversion still and repatriation of funds. to that end, the Us dollar as a reserve currency has distinct advantages. The biggest impact would be weakness of emergin market currencies that cannot withstand money flows out of their currencies to the extent the Euro our Yen can. General dollar strength until a replacement is decided upon by the free markets.

JW.: What’s the best advise to give to an individual trader and to a semi professional trader who wants to enter the FX fund management industry?

rM.: stay disciplined and trust your research. Watch your risk controls and build a track record. After the track record is built, be prepared to be surprised by all of the non-trading business decisions that you will face running an institutional class asset management firm.

FXFX MANAGERS


Grammatical evolutionautomated generation of trading rules

in recent years we have witnessed a steep increase in the application of natural computing techniques in finance.

in this article we will discuss the application of Grammatical Evolution, in our view one of the most promising and flexible evolutionary computing approaches to ForEX financial time series. We will build a trading model using Grammatical Evolution on the 60 minute time frame series of GBPUsd, EUrUsd and UsdCHF over 88 trading weeks and present the results. We will also propose the set up of a number of portfolios to exploit the potential of the rules emerged via Grammatical Evolution. We will not focus on programming techniques as our aim is to show the logic that lies under this new and interesting approach and its potential.

Backgroundif we assume that all the information available for a specific market is captured by the equilibrium market price arising from the interaction of rational agents, there would be no point in trying to identify price dynamics or patterns because there would be no predictability. But we don’t believe in the Efficient Market Hypothesis in its strict formulation and, starting from this premise, we do our research.

in finance the adoption of techniques to evolve or extract trading rules from a time series finds its theoretical foundation in the weakness of the premises of the Efficient Market Hypothesis: many researchers question the rationality of market agents and the fact that all the information that concur to price equilibrium are disposable and perceived by all the agents in the same way. other hypothesis that

involve relative efficiency of markets, like The Adaptive Markets Hypothesis (AMH), where market efficiency emerges as an evolutionary process through competition between agents justify the adoption of evolutionary expectational models and represent, in our view, a better framework in approaching financial markets.

natural computing can be seen as a way of developing programs and algorithms, taking inspiration from real world phenomena. Grammatical evolution specifically is a particular Genetic Programming approach to generate computer programs (in our case trading rules) in an arbitrary language defined by the user. We refer to Genetic Programming as to an evolutionary computation technique where a population search based approach is used to evolve a solution to a certain

FX TRADING SYSTEMS


problem. to make things clearer to non specialists we will describe the genetic process as a way to build a ‘valuable’ trading rule for a specific time series over a period of time. We will present some examples in the following part of the article that should help in understanding how the subject works.

We can say that Genetic programming mimics the darwinian principle of evolution to evolve a solution to a specific problem. real world phenomena are characterized by uncertainty and noisiness in dynamic environments and are modified by the interaction of multiple agents. For those very reasons a natural Computing approach seems well suited for financial where similar conditions are met.

Hands on grammarAfter a brief theoretical introduction we will describe the process of setting up a Grammatical Evolution-based trading system. As we briefly mentioned before, Grammatical Evolution is a form of genetic programming that allows the user to evolve computer programs, rule sets or more generally, sentences in any language. it is a methodology that allows us to evolve the solution to a specific problem (as happens in genetic programming) with a plus: we can define the grammar, i.e. the shape in which the solution is to be expressed.

our goal is to produce a trading rule for a specific time series over a time period. We don’t know how this rule will look like, we just know which are the building blocks that will compose it. in our case we chose some well know technical indicators and a proprietary one (see table 1)

TECHNICAL INDICATORSADX (arg) Average Directional MovementROC (arg) Rate of Change indicator.RSI (arg) Relative Strength Index indicator.Stdev (arg) Standard Deviation indicator.ATR (arg) Average true range indicaror.SMA (arg) Simple Moving Average indicaror.MIN (arg) MAX(arg) Minimum and maximum.HT (arg) HT Trendline indicaror.LTS (arg1,arg2,arg3) Proprietary trend following–mean revertingTable 1

We tried to use as few indicators as reasonable in respect to the principle of parsimony though representing volatility, directionality, momentum and breakout. Each indicator can take one or more arguments accordingly to its structure, for example sMA takes one argument which is the length of the moving average considered.

in grammatical evolution we define a ‘Grammar’ that determines the shape of every bit of the solution that has to be evolved, we will not focus on an in-depth analysis of the grammar writing process because this falls out of the scope of this article but, we would still like to give an idea of the logic laying beneath it.

For instance, we define a <trading Condition> as a combination of the mentioned indicators with <arg>, the function argument, being an integer number between 1 and 100, < operator > being ‘> greater than’ or ‘< lesser than’ and < num > being a floating number between 0 and 100. the grammar would look a bit like this:

Here are some examples of <trading Condition> generated by the algorithm following the previous grammar:

those trading conditions can be combined together by the algorithm in ‘and’ and ‘or’ logic to build sentences like:

<trading Condition> = <indicator (arg) > <operator> <num>

indicator = ADX (arg), ROC (arg), RSi (arg), Stdev (arg), AtR (arg), SmA (arg), min (arg), mAX(arg), ht (arg), ltS (arg1,arg2,arg3)

<arg>= integer number between 1 and 100

<operator>= ‘<’, ‘>’<num>= floating number between 1 and 100

<trading Condition>= ROC (20) > 25.3<trading Condition>= RSi (89) > 12<trading Condition>= AtR (15) < 3.1

<trading Condition>= and (AtR (15) < 3.1, RSi (89) > 12) where both AtR (15) < 3.1 and RSi (89) > 12 must be true,

<trading Condition>= or (RSi (89) > 12, ROC (20) > 25.3) where RSi (89) > 12 or ROC (20) > 25.3 must be true,

<trading Condition>= or (and(AtR (15) < 3.1, RSi (89) > 12), ROC (20) > 25.3) a combination of ‘or’ and ‘and’ logic.


FXTRADING SYSTEMS

Last step is now to define the grammar of the solution, our trading system. We want to generate a trading rule, so we imagine two possible outcomes in terms of grammar: a simple buy and sell rule that reverses the position at every new signal, and a more complex rule that has a customized exit rule for the buy and the sell signal:

The computer can now evolve a solution combining trading rules accordingly to the grammars.

A set of rules that combines the two bits of grammar described above would look like this* :

*(please note that the following rule is meaningless and for demonstration purpose only):

Well this is a trading system!

The evolutionary processHow does the genetic programming algorithm evolve the best rules? in the beginning it generates a ‘population’ of trading rules randomly. Every single rule, like the one we showed in the example, is called ‘individual’. A

population can consist of a number of individuals defined a priori by the user. Every single individual is then evaluated against a ‘fitness function’. The fitness function returns a value that quantifies how that individual is doing well in relation to a specific problem. in our case the fitness function can be the profit generated by a trading rule on a specific time series or a risk adjusted measure of profit. specifically we use a proprietary combination of profit, draw-downs, max draw-downs and cumulative profit curve shape. Those individuals (rules) of the population that have the highest values of fitness function become the parents of a new generation of individuals. in that way winning bits of rules are mixed together to generate new rules. some random variability is added so that there is a mutation in each new generation that will be not only made of the brute mix of parents’ genetic inheritance. it is very obvious that this evolving process

mimics the darwinian evolutionary process. it turns out that this is an extremely powerful and efficient way to explore a space of solutions that cannot be searched by a brute force combination of parameters because the dimension of the space of solutions would be huge and the exploration of it all would take a significant amount of time.

Using this approach at the end of each optimization we have a number of individuals with a high fitness value. That means we have a set of good trading rules optimized for the time series we were using during the evolution. As every trading system expert knows, the tricky part is yet to come. The fact that we have found good rules for a time series in a specific time period, no matter how sophisticated our approach is, doesn’t mean we have found trading rules that are able to generalize well on unseen data.

(<iF> <trading Condition> then BuY), (<iF> <trading Condition> then Sell) – Simple buy and sell trading system-

(<iF > <trading Condition> then BuY), (< iF > <trading Condition> then StOPlOng)

(<iF > <trading Condition> then Sell), (< iF > <trading Condition> then StOPShORt)

-trading system with stops-

iF( or (and (AtR (15) < 3.1, RSi (89) > 12), ROC (20) > 25.3) then BuY

iF ( SmA (30) < Close) then StOPlOng

iF (and (ROC (55) < 50 , RSi (56)< 96), StDeV ( 20) > 2.3) then Sell

iF ( and ( AtR( 55) < , StDeV (20) > 2.3) then StOPShORt




FXTRADING SYSTEMS

The dataThree years of data have been used, from december 2005 to november 2008. We analyzed the 60 minute time frame series of GBPUsd, EUrUsd and UsdCHF. The data has been collected by our automated trading engine and outliers have been cleaned. slippage for each cross is the average value of the real slippage we had in our real money automated trading experience and is as follows:

0.6 pips on EUrUsd1.1 pips on UsdCHF1.6 pips on GBPUsd We have chosen the 60 minutes time

frame because we wanted to have a high frequency approach and, at the same time, reduce the impact of a potential widening in market spreads. The limited number of trades generated by a 60 minutes model, compared with a 5 or 10 minutes one gives us more confidence about the stability of results against a potential worsening of market conditions.

Training and Testing methodologyone of the most complex issues in financial time series analysis is the choice of the training and testing time span. Financial time series may exhibit persistence in price dynamics for enough time to exploit them with profit but are also subject to sudden changes in volatility and price dynamics because of a wide variety of factors that range from financial to economical to social or technological. in our test we use a proprietary methodology where we train the time series on a variable time span that ranges between 3 and 12 months according to the persistence of some time series volatility indicators. The rules extracted in each time span are then applied for the following 4 weeks.

so basically we used a sliding window approach where at time t we extract the trading rules (in our example using Grammatical Evolution) on a time span ranging from t-x to t where x={12 weeks,24 weeks,36 weeks,48 weeks} and trade them from time t+1 to time t+4. We repeat the process till the end of the series. This way, considering that a bit more than one year of time series is used for the first train, we have 88 weeks left for testing purpose. That is, in our case, 22 periods of 4 weeks to test the real market performance of the system.

Cross/Individuals Return %EURUSD ind 1 27.78EURUSD ind 10 5.40

EURUSD ind 25 7.00EURUSD ind 50 3.44GBPUSD ind 1 20.07GBPUSD ind 10 14.54GBPUSD ind 25 14.63GBPUSD ind 50 11.88USDCHF ind 1 40.68USDCHF ind 10 7.65USDCHF ind 25 8.47USDCHF ind 50 5.27

Table 2

At every evolution we kept the best 50 trading rules and traded them applying the average real market slippage we had with our real-money automated trading system in the last three years. The results will be presented for each Cross and split into 4 groups: in the first group we average the returns generated by the average of all the 50 rules, in the second group we average the first 25 rules, in the third the first 10 rules and in the last we consider the returns generated by the best rule only. rules are ranked according to their training fitness value.

ResultsPlease refer to chart 1, 2 and 3 for the cumulative returns on each cross for each group. results are summarized in table 2.

results already include slippage and, they

are in leverage 1:1 and must be considered in that perspective. We notice that every cross has a positive cumulative profit at the end of the testing period. it is also interesting that the best individual is always the best performer and is producing significantly higher returns. The 25 individuals group slightly outperforms the 10 group on each Cross considered. The 50 individuals group is always the worst performer. This suggests that the algorithm, combined with the fitness function and the training methodology, are well suited to exploit potential trading rules, as the performance on unseen data is increasing as the training fitness value increases.

A small portfolio experimentEven if the best individual has such a better performance, it is always risky to allocate the whole capital on a single rule, even if each Cross has its own best rule on each time span, so we decided to simulate the

outcome of two to test the impact of using m u l t i p l e rules at a time: a first p o r t f o l i o n a m e d “A v e r a g e portfol io” where 25% of the capital is allocated on each of the group mentioned above and split between the three Cross, a second portfolio named “Best Portfolio” where capital is divided only between the best individuals of each cross. (please see table 3 and 4 and chart 4).

AVER PORTFOLIO EURUSD GBPUSD USDCHFbest individual 33% of 25% capital 33% of 25% capital 33% of 25% capitalbest 10 individuals 33% of 25% capital 33% of 25% capital 33% of 25% capitalbest 25 individuals 33% of 25% capital 33% of 25% capital 33% of 25% capitalbest 50 individuals 33% of 25% capital 33% of 25% capital 33% of 25% capital

BEST PORTFOLIO EURUSD GBPUSD GBPUSDbest individual 33% of capital 33% of capital 33% of capitalTable 3

PORTFOLIO RETURN %

CALMAR RATIO

AVERAGE 13.90 4.77BEST 29.51 7.74Table 4

results favor the ‘best’ portfolio in terms of absolute profit and Calmar ratio. Anyway, the differentiation induced by using a combination of 50 individuals, even if the best ranked ones are over-weighted, is worth in our view the loss in performance, should a drastic change in price behavior occur. Facing an unknown change with a portfolio of tens of individuals, rather than 3, is reassuring and must be considered as an option.

ConclusionsEvolutionary algorithms are becoming more and more popular in the financial community thanks to their flexibility and efficiency in exploring huge solution spaces and deliver interesting results, the theoretical premises lying behind this

approach are intuitively compatible with a dynamic and complex phenomenon like the price discovery process represented by a financial time series. A point that deserves more attention is the quick adaptation to a dynamic environment and the ability to detect abrupt changes in price behavioural patterns and some work has yet to be done in this direction. the approach used in this article of a rolling train-test window is quite native and has some drawbacks but, was mainly intended to illustrate the potential and the logic of genetic programming, focusing on the flexibility of grammatical evolution.

Luca Taroni 46 FX TRADER MAGAZINE April-May 2009


As the financial markets have lurched from one piece of bad news to the next over the last 9 months, there appears to be one segment that seems to be flourishing: the new-issue corporate bond market.

Bonds are simply a form of ioU, issued by supra-national organizations, governments, banks, corporations and some special-purpose entities to help finance their operations. Purchasers of bonds come from all categories of potential investors, and range from the most sophisticated fund managers in the world, to corporate treasuries, to individuals.

This type of investment usually has a stated maturity, and infers that there is some sort of security of capital repayment at maturity. Combined with the provision of a regular source of income during the term of the bond (a coupon), these investments have features that make them attractive for most types of investors. There is always a risk of default (the possibility that the issuer of the bonds will not have the means to repay the debt at its scheduled maturity date), and there is also a likelihood that the price at any given time during the life of the bond will be different (higher or lower) than the price paid at the time of purchase.

A mantra for all investors should

be the words “balanced portfolio.” A balanced portfolio is likely to contain shares, property, cash, perhaps valuables or commodities, and: Bonds. The current attraction of bonds for investors worldwide has been heightened by plummeting equity markets, the end of the property bubble, the uncertainty surrounding the financial solidity of many banks, and volatile commodity prices. Corporate bonds seem to offer some refuge from this sea of volatility at the moment, and provide a higher

rate of return that bank deposits or government bonds. A specific example of this might be a bond recently issued by roche (the giant pharmaceutical company) that pays a 4.625% coupon annually during the 4-year life of the issue. roche raised EUr 5.25 billion with this bond as part of the war chest it is building in its effort to acquire Genentech. on the surface, the roche issue had a lot of positives for investors: a strong corporate name as borrower (with high ratings), a medium-term

maturity (4 years) and a comparatively generous yield of 4.625% (vs italian government bonds @ 3.00% approximately). Clients put in orders for nearly EUr 10 billion of this issue, but the company “limited” its size to EUr 5.25 billion.

The roche issue is one example of more than 40 corporate bond issues that have come to the market in the last few months and met with similar investor demand (although it is arguably the best of the bunch so far this year). Another category of bond that has met with massive investor demand has been the type issued by banks, but with the added (necessary) attraction of being guaranteed by governments. These bonds differ from the one described above from roche in that they have been explicitly guaranteed by the government of the country where the issuing bank has its head office (primarily the Us, the UK, and ireland to date). in return for the relative comfort of a sovereign guarantee, investors have accepted lower coupons on this set of bonds (a good example of this would be the 2.75% 3-year bond issued in sterling this week by Lloyds Bank which carried the explicit guarantee of the UK treasury).

Leaving aside any technical questions the above information might

Why are bonds attracting retail and high net-worth investors?


FXFOCUS ON BONDS

be bringing to mind, there should be other questions that start to turn in your head. Why would a bank want/need a government guarantee to help it raise money? Why would a company like roche need so much money? Why would investors be so keen to lock in their savings for such relatively long periods in these times of uncertainty and with such relatively low interest rates? now the plot thickens!

These are all valid questions, and the markets would likely be less volatile if more investors asked these questions more openly, more often (and more financial advisors knew what they were actually selling). However, recent history has shown us all too clearly

that very few investments get the amount of reasoned reflection that they require, and that everything is not as clearly explained as it might seem

on the label. Whether it is Parmalat, Lehman, Argentina, Enron, Madoff or iceland, these examples evoke images that have little to do with latte, pampas or thermal spas that one could hope would be the associations made by the average person in the street.

in response to the questions above and other similar ones you might be asking, investors are generally seeking a greater

degree of security than they had been looking for in recent years, and these bond issues respond to that desire/fear. does that make them good investments? not

necessarily. does that make them the right investment for everyone at the moment? definitely not. However, they do provide an option for investors when there are such

bad market conditions for most other types of investments. Within the continuing climate of volatility, uncertainty and low interest rates, bonds are likely to be a bright spot in the financial markets provided that the current rush to bonds doesn’t create its own little bubble…

D. Roy Fraser

Very few investments get the amount of reasoned reflection that they require

FX FOCUS ON BONDS


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The Magic of Elliott Wave Analysis

i have been practicing Elliott Wave Analysis for over 25 years, and have made some astounding calls that came true. But i cannot honestly say that i was able to turn a mere $10,000 into a million dollars. Yet, i can confidently say that there are very few technical approaches to dealing with the uncertainties of the market place as efficiently as does the Elliot Wave Principle.

i am not going to give you the rules and guidelines governing the practice of Elliot Wave Theory. There are ample resources in the web that you can access at the click of your mouse. What i will do, instead, is to give you one example now, and show you how the magic of Elliot Wave Principle works in the Forex market.

You see here two charts of sterling Pound (GBP/Usd). The first is a monthly chart going back to the early 1980s. The second is a daily chart going to oct 2007. The beauty of Wave Principle is that it works equally well in the monthly chart as it does in the 5-minute chart! Having said that, i must also add that you should not try to day-trade using the monthly chart! For example, the monthly chart suggests that our long-term target for the Pound is around 1.3300

(We have already reached 1.3498) but the daily chart points to a significant recovery, perhaps reaching as high at 1.6170 before down. of course, there are several risk levels on the way, for example, it might run into considerable selling pressure near 1.4900.

But let us first look at the monthly chart and see how the waves unfolded. Let us suppose that we are now in the early

1990s and have already seen the first big move from 1.0520 to 2.0045 (Point A). When the second attempt failed to sustain above that level, we should have anticipated a swift move down. remember that the third step of any progression is always a powerful move. We could have easily calculated that a 61.8% retracement of the Wave “A” would lie at 1.4158. The move actually finished at 1.4063. next consider the “c” wave that went from 1.7366 to 1.3677. Believe

it or not, but that move was just 7 pips short of the 61.8% measure of the “a” wave. But the wonder doesn’t stop there. Wave “B” that went from 1.3677 to 2.1161 was only 2 pips short of 78.6% of wave “A”. The Elliot Wave Principle asks us to always be on the look out for Fibonacci relationships between alternating waves.

TECHNICAL ANALYSIS FX


“Can anyone parlay a $10,000 capital into $1,000,000 in a year? in five years? if so, how do you do it and what are the risks involved?” – robert Balan

now let us turn to the daily chart. This is a lot more interesting. As you can see from the comments on the chart, one could have placed a low-risk “buy” trade near 1.7450 as it marked a 161.8% projection of the first wave down. one of the problems that many beginning-analysts face is how to pick a level and call it the end of a certain wave? For example, how did i label the 1.7450 level as a mini wave 3? With hind sight it all looks so good, but how on earth can one figure out that we will not break directly down? (see for example how the 261.8% level at 1.5628 did not hold). Welcome to the real world of Elliott Waves! The key to lasting success in the business of trading is to be honest to your paradigm. Follow your rules (whatever they may be) to the letter. The biggest sin that a trader can commit (second only to not having a stop loss) is to keep changing his rules.

take a look at the chart again. When you get a fast sell off, you should calculate various projections and keep them by your desk. i would have known that 1.7450 was a likely (but not certain) support. i would not buy there the first time. typically in a fast moving market, we will always get a retest of the lows. if the market stabilized near a Fibonacci projection at the first try, i would place a small ‘buy’ order near the prior low with a stop just a few pips below that low. As you can see, we got a second test of 1.7450 two or three days after the first try. since the buying interest was strong at that level, the trade paid off handsomely. (Another tip: depend on daily charts more than hourly charts to figure out supports and resistances).

Let us look to the future now. Why do i think we could go higher to around 1.6170? First of all you should understand that in order to make money, it is not so important to know the medium term targets as it is to know the general

direction! so what if we don’t get as far as 1.6170. Most traders would be just as happy to catch a move to 1.4900.! Anyway, back to the question. We saw that Wave (2) at 2.097 was a ‘simple’ correction. This means there is a high probability for wave (4) to be a complex one. We have already seen that the “B” wave (as labeled by me) is an irregular one, with the low coming well below the end of

the Wave (3). if you accept this count as valid (and remain truthful to that count until proved wrong) then you should look for the Wave “C” within the Wave (4) to go well above the top of the wave “A.” Besides, the second test of the low seen AFtEr posting the “B” wave bottom was unable to break the prior low. And finally, we not only saw a strong

move higher, but it has managed to break above a declining (green colored) downtrend line. These are just some of the reasons why i am looking for sterling to continue moving higher.

it is vitally important to have an open mind about these things. Consider this. i have a market reputation and will look silly if the Pound stops climbing and goes down directly. should i allow that to bother me? if one only worries about being ‘correct’ in making market calls, one will never be a good trader. A trader has to study his charts and make the most educated prediction about what will happen next. He should then execute his plan of action without wavering one bit. This includes having an affordable stop-loss, as well as plans to take profits along the way. There is no other way to riches.

Ramki (N.Ramakrishnan)


TECHNICAL ANALYSISFX


MAJors rEPortTREND EURO, US DOLLAR, YEN

SPOT PRICE 23/03/2009 01/01/2009 ∆% 01/01/2008 ∆%

EURUSDUSDJPYEURJPY

1.356697.24131.97

1.395290.79

126.65

-2.8%7.1%4.2%

1.4583111.79163.04

-7.0%-13.0%-19.1%

DOLLAR/YEN

dollar/yen has been moving in a major down trend for several decades: at the beginning of the seventies it was trading at around 350, since the mid-eighties it went stably below 175. After having collapsed to a historical low at 79.75 in April 1995, the dollar started a strong reversal, reaching a top at around 147.65 in August 1998. From that level, the major down trend resumed, with a series of falling highs and “raids” below the key support at 115 (a level repeatedly supported by the Bank of Japan’s interventions). the dollar reached a bottom at around 101.35/85 at the end of 1999, level tested again at the end of 2004.

the break of that support during last year, caused a new sell-off, that led the dollar towards 87 at the beginning of this year. the rally started in February has reached the psychological resistance at 100: the pair then consolidated above 93.55. A break above 100 would signal a prosecution of the rally, with first target in area 103.75-104 and extension towards the key resistance area 110-115: only above that resistance (unlikely) would the dollar start appreciating remarkably in the coming months. Lost of momentum below 92-93.55, targeting the January 2009 low at 87.

TREND SUPPORTS SPOT PRICE RESISTANCESTrend 3-6 months up S1 92-93.55

97.24R3 110,00++

Trend 6-12 months side S2 87+ R2 103,75-104,00+Trend 12-18 months side S3 79.75++ R1 100+

Technical analysis FX


EURO/DOLLAR

Euro/dollar was first traded in Januar y 1999, at around 1.1800-1.1900 and fell to a historical low at 0.8231 on october 26th, 2000. From that bottom, the euro began accumulating and – since summer 2002 – moving upwards, entering progressively a major up -trend and reaching a top at 1.6038 on July 15th, 2008 (+95% vs. the historical low). the fall below the strong support at 1.5275 on Aug ust 8th, 2008 ( level that had supported the pair in the period April-July) caused a major reversal , with a fast decline towards 1.3900, followed by a pull-back to a top at 1.4866 on september 23rd and a new sell-off to a bottom at 1.2330 on october 28th. in mid-december, a strong rally brought the pair, in just a week, to a top at 1.4719. then it started going down again and fell to a bottom at 1.2460-1.2514, area that has been supporting the pair in the last months ( in a sideway range below

the strong resistance in area 1,3100-1,3300). in mid-March, the pair overcome the resistance at 1.3100-1.3300 and jumped over 1.3700 (next resistance in area 1.4000-1.4350). the quantitative easing policies adopted by the Fed ( i.e. printing dollars in order to buy government bonds) are behind the renewed weakness of the dollar. such debility could continue in the coming months, especially against the euro (due to the “technical” difficulties the ECB will have to face to take such policies itself ). the euro would lose strenght against the Us dollar only should it fall again below 1.3000, and the pair would enter in a down trend only below 1.2330-1.2460 (unlikely). For the coming months, the euro would start appreciating remarkably against the dollar only above the critical resistance area 1.4850-1.4950 (unlikely at the moment).

TREND SUPPORTS SPOT PRICE RESISTANCESTrend 3-6 months up S1 1.3000-1.3100++

1.3566R3 1.4850-1.4950++

Trend 6-12 months up-side S2 1.2720 R2 1.4000-1.4350+Trend 12-18 months up-side S3 1.2330-1.2460++ R1 1.3735

Technical analysisFX


EURO/YENThe cross euro/yen was first traded in January 1999, at around 132.50-135.50, and fell to a historical low at 88.96 in october 2000. From the bottom, the euro began moving upwards, entering progressively a major up-trend, and reaching a historical high at 169.95 in July 2008 (+91% vs. the october 2000 bottom). The strong depreciation of the yen during last years has been mainly caused by the so called “carry trade”, i.e. the funding in low-yield currencies like the Japanese yen with the contextual reinvestment in asset classes in other currencies (i.e. stocks and bonds in euro, Australian and American dollars, etc.). After the burst of the real estate and financial bubble – begun in the 2007 summer, with an acceleration after september 2008 – a progressive strong disinvestment from stock Exchanges around the world led to massive yen buying in order to square up carry trade positions. This has provoked a crash of euro vs. yen, driven by a double source: the fall of euro against the dollar and, at the same time, the decline of the Us dollar versus the yen. After the break of 156 in september 2008

– in correspondence with the trendline that sustained the major up trend), the cross collapsed to a low at 113.65 on october 27th, 2008. in the following months, the cross moved sideways, above that level and below 131. in January 2009, the euro reached a new low at around 112.10 (-34% form the historical high). in the last months the cross has been bouncing back, and has overcome the resistance in area 130-131 that had contained the euro movement since the end of october. if the cross remains above 125.50 and confirms the break of 130-131 the outlook remains bullish, with a possible rally towards the resistance area 140-142, with extensions in the coming months towards 150. Lose of momentum below 122 (not very likely), targeting the January lows at 112.10. A break of the January 2009 bottom (unlikely) would cause a sell-off, targeting 106 and then the important psychological support at 100.

Maurizio Milano

TREND SUPPORTS SPOT PRICE RESISTANCESTrend 3-6 months up S1 125.50

131.97R3 150++

Trend 6-12 months up S2 122.00 + R2 145Trend 12-18 months side S3 112.10++ R1 140-142+

Technical analysis FX


Current level Major trend Major target Trend change levelEUR/USD 1.3575 Down 1.1000 1.5200USD/JPY 95.75 Down 75.00 115.00USD/CHF 1.1250 Up 1.3000 1.0000GBP/USD 1.4425 Down 1.2900 1.7100USD/CAD 1.2375 Up 1.4500 1.0900AUD/USD .6900 Down .5400 .8600NZD/USD .5625 Down .4500 .7200EUR/JPY 130.00 Down 100.00 150.00GBP/JPY 138.25 Down 100.00 180.00AUD/JPY 66.00 Down 45.00 85.00EUR/CHF 1.5275 Down 1.3300 1.6250EUR/GBP .9400 Up 1.1000 .7600EUR/NOK 8.65 Up 10.85 8.15EUR/SEK 11.13 Up 12.60 9.55

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MAJOR TRENDS AND TARGETS FOR THE MAJOR FX RATES

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TECHNICAL ANALYSIS FX

EUR/USD lost almost a quarter of its value during the July to october 2008 decline, taking it down from a new all-time traded high at 1.6039 on 15th July to a 2 ½ year low at 1.2329 on 28th october. this retreat retraced close to 50% of the 8 year rise from the october 2000 all-time traded low at .8232. several weeks of consolidation followed the 1.2329 low, giving way to a strong corrective recovery which briefly exceeding the 61.8% retrace of the 1.6039-1.2329 decline to reach a peak of 1.4721 in mid december 2008. However, a sharp reversal occurred from that high, spot-on the 260 day (1 year) moving average. An almost full retrace of the two-month recovery phase followed, the failure to leave a higher low by former resistance at 1.3299 & 1.3079 (october / november 2008 rally tops) ended the immediate possibility of a further recovery, warning instead of 1.4721 marking a significant lower top below the 1.6039 peak for a potentially quite sizeable further decline over coming months. However,

over the short-term, a partial unwinding of recent losses from 1.4721 has emerged, clearing with ease the 1.3180-1.3323 resistance area, where the 65 day (3 month) moving average and 38.2% retrace of the 1.4721-1.2459 decline had merged. this suggested a return toward the 1.3829-1.3857 area (mid december 2008 setback low / 61.8% retrace of 1.4721-1.2459), without ending the possibility of an eventual further decline over coming months in the direction of 1.1011. this marks a 100% projection of the July-october 2008 decline from the december 2008 lower top as well as being close to the base of a projected bear channel, produced by paralleling the 1.6039 & 1.4721 highs with the 1.2329 low. successfully clearing the 1.3857-1.3788 resistance area will avert the immediate danger of a fresh slide and point instead to a retest of the 1.4721-1.4862 area where the december and september 2008 highs were left.

EUR/USD


EUR/CHF fully retraced the 6 year rise from 1.4402 in september 2001 which peaked at 1.6828 in october 2007 in a little over a year, dipping through 1.4402 to a new all-time traded low at 1.4322 on 27th october 2008. A strong recovery followed, 1.5881 being reached on 15th december 2008, slightly over the 61.8% Fibonacci retracement of the previous 1.6828-1.4322 decline at 1.5871. the speed and extent of the reversal from 1.5881, which was also just under the falling 260 day (1 year) moving average, warned that the underlying trend was still firmly down, with potential for start of a further sizeable decline. this looked even more likely in early March when the 1.4660-1.4710 support area ( January 2009 / november 2008 lows) was breached, but since reaching a new 2009 low at 1.4586 on 6th March a strong recovery has been enjoyed. As yet, this is classed as corrective but we need to see a lower

top form below the december 2008 recovery peak at 1.5881, ideally by the 8 month downtrend / 260 day moving average, in order to maintain the underlying bearish trend for an eventual breakdown through 1.4322 to yet new all-time lows. in the event that the 1.4586 and 1.4322 lows are indeed eventually lost, we see potential for a move toward the 1.33 line over the coming 3 to 6 months, with the 1.38 region an interim target. on the upside, in the event that the multi-month downtrend and year-long moving average are both overcome, then a return to and possible overshoot of the december 2008 recovery peak could ensue. However, any higher than the 1.60-1.62 area is likely to switch the medium-term odds in favour of a prolonged recovery rather than an impending return to weakness.

Steve Jarvis

EUR/CHF




Country Flag USD Spot Last vs USD % Ch 3M % Ch 12M 12mth High 12mth Low

Eurozone EUR= 1.3585 -3% -13% 1.5987 1.2457

UK GBP= 1.4603 0% -27% 2.008 1.3746

Japan JPY= 98.11 8% -2% 110.49 87.31

Switzerland CHF= 1.1221 5% 12% 1.2241 0.9843

Australia AUD= 0.701 2% -24% 0.9787 0.6018

Canada CAD= 1.2268 0% 21% 1.2995 0.9832

New Zealand NZD= 0.5775 0% -28% 0.8097 0.493

Sweden SEK= 8.0307 1% 33% 9.2927 5.838

Norway NOK= 6.5027 -8% 26% 7.2227 4.953

Iceland ISK= 116.54 -7% 55% 147.55 71.67

Israel ILS= 4.1518 8% 19% 4.236 3.213

South Africa ZAR= 9.4447 -2% 18% 11.62 7.2025

Egypt EGP= 5.6325 2% 3% 5.694 5.2825

Saudi Arabia SAR= 3.7499 0% 0% 3.7685 3.7115

Czech Rep. CZK= 20.119 8% 24% 23.438 14.404

Poland PLN= 3.3475 16% 48% 3.9003 2.0221

Hungary HUF= 220.98 18% 35% 251.64 143.19

Russia RUB= 33.455 15% 41% 36.3438 23.1531

Turkey TRY= 1.6516 9% 31% 1.806 1.1512

China CNY= 6.8309 0% -3% 7.083 6.8108

Hong Kong HKD= 7.7499 0% 0% 7.8142 7.7483

Singapore SGD= 1.5062 4% 9% 1.5562 1.3476

Taiwan TWD= 33.804 2% 12% 35.21 29.996

India INR= 50.57 4% 26% 51.96 39.75

South Korea KRW= 1330.4 2% 36% 1570.1 973.5

Thailand THB= 35.31 1% 12% 36.26 31.04

Malaysia MYR= 3.624 4% 13% 3.726 3.1305

Indonesia IDR= 11520 5% 25% 12100 9070

Philippines PHP= 48.13 1% 17% 49.94 41.3

Mexico MXN= 14.2218 6% 33% 15.555 9.858

Brazil BRL= 2.237 -6% 29% 2.511 1.5591

Chile CLP= 571.4 -9% 27% 682.5 430.6

Venezuela VEB= 2144.6 0% 0% 2144.6 2144.6

Colombia COP= 2388.9 8% 31% 2608.15 1655.9

Levels Date:26-Mar-09 Source: Thomson Reuters

FXINTERNATIONAL DATA

FX sPot Monitor

Country Flag Central Bank Rate Name Actual Previous

USA FED Fed funds 0-0.25 0.00

Eurozone ECB Refi 1.50 1.50

UK BOE Bank Repo 0.50 0.50

Japan BOJ O/N Call 0.10 0.10

Switzerland SNB 3 mth Libor 0.25 0.50

Australia RBA Cash 3.25 3.25

Canada BOC O/N Funding 0.5 1.00

New Zealand RBNZ Cash 3.00 3.50

Sweden Riksbank Repo 1.0 2.00

Norway Norges Bank Depo 2.00 2.50

Iceland CBI Policy 17.0 18.00

Israel BOI Short Term Lending 0.5 0.75

South Africa Reserve Bank Repurchase 9.5 10.50

Egypt CBE O/N Depo 10.50 10.50

Czech Rep. CNB 2 Week Repo 1.75 1.75

Poland NBP 28 Day Intervention 3.75 4.00

Hungary MNB 2 Week Depo 9.5 9.50

Russia CBR Refinancing 13.00 13.00

Turkey TCMB O/N Borrowing 10.50 11.50

China PBC 1 Year Lending 5.31 5.58

Taiwan CBC Discount 1.250 1.250

India RBI Repo 5.0 5.50

South Korea BOK O/N Call 2.00 2.00

Thailand BOT Repo 1.5 2.00

Indonesia BI BI 7.75 7.75

Philippines BSP Repo 4.75 5.00

Mexico BDM Target 6.75 7.50

Brazil BCB Selic 11.25 12.75

Chile CBC MPR 2.25 4.75

Levels Date: 26-Mar-09 Source: Thomson Reuters

CEntrAL BAnKs

FX INTERNATIONAL DATA


3 Month Days since Poll Poll Median Poll Min Poll Max Poll Mean Std Deviation Spot@Poll Date

EurUsd 22 1.25 1.15 1.5 1.259 0.064 1.2635

GbpUsd 22 1.405 1.29 1.6 1.414 0.067 1.4163

AudUsd 1 0.63 0.55 0.71 0.629 0.0346 0.6976

UsdJpy 22 96 85.2 110 96.2 5 99.08

UsdChf 22 1.19 1.05 1.31 1.19 0.049 1.1708

UsdCad 22 1.27 1.18 1.4 1.276 0.044 1.2741

EurJpy 22 121.5 104.7 150 121.1 8.7 125.25

EurChf 22 1.485 1.416 1.613 1.494 0.039 1.498

EurGbp 22 0.892 0.8 1.02 0.892 0.042 0.8918

GbpJpy 22 137.8 113.5 155 135.9 9.6 140.35

1 Year Days since Poll Poll Median Poll Min Poll Max Poll Mean Std Deviation Spot@Poll Date

EurUsd 22 1.28 1.087 1.62 1.299 0.125 1.2635

GbpUsd 22 1.5 1.27 2 1.518 0.138 1.4163

AudUsd 1 0.685 0.54 0.85 0.672 0.0623 0.6976

UsdJpy 22 100 75 120 100.9 9.4 99.08

UsdChf 22 1.18 0.95 1.475 1.192 0.112 1.1708

UsdCad 22 1.21 1.1 1.44 1.231 0.08 1.2741

EurJpy 22 128.5 88 194.4 131.2 16.6 125.25

EurChf 22 1.545 1.416 1.68 1.54 0.054 1.4798

EurGbp 22 0.86 0.709 0.979 0.859 0.055 0.8918

GbpJpy 22 152.4 107.2 240 152.9 19.1 140.35


FXINTERNATIONAL DATA


GDP CPI Industrial Production Unemployment

y-o-y y-o-y y-o-y level

USA -6.20 0.40 -1.40 8.10

Eurozone 0.60 0.40 -3.50 8.20

UK -1.80 0.90 -2.60 6.50

Japan -3.30 0.00 -10.00 4.10

Switzerland -0.60 0.20 3.10

Australia 0.30 3.70 5.20

Canada -3.40 0.70 7.70

New Zealand (partecipation) -0.10 3.40 69.30

Sweden -4.90 0.90 -2.50 8.00

Norway 1.30 2.50 -1.30 2.70

South Africa 1.00 8.60 -11.10 21.90

Czech Rep. 0.70 2.00 -23.30 7.40

Poland 2.90 3.30 -14.30 10.90

Hungary -2.30 3.00 -22.90 8.40

Russia -7.30 1.70 -13.20 8.50

China 6.80 -1.60 3.80

India 7.10 9.80 -0.50

Mexico -1.60 0.49 -11.10 5.30

Brazil 1.30 0.55 -17.20 8.20


EConoMiC dAtA

FX PoLL

Stock Indices Last % Ch 6M % Ch 12M Commodities Last % Ch 6M % Ch 12M

Gold 933.1 6.23% -2.14%

MSCI World 831.34 -34.23 -42.74 Silver 13.49 1.50% -26.76%

Dow Jones Ind. 7749.81 -29.69 -38.16 Brent DTD 51.5 -49.15% -49.97%

S&P 500 813.88 -32.02 -40.28 WTI 52.16 -51.15% -50.71%

Nasdaq 100 1236.66 -26.72 -32.22

Eurostoxx 50 2149.18 -32.99 -40.84 Bonds Last % Ch 6M % Ch 12M

UK FTSE 100 3900.25 -24.95 -31.44 5Y Euro 2.421 -1.471 -1.039

Dax 4223.29 -31.58 -35.27 10Y Euro 3.137 -1.019 -0.728

Cac 40 2893.45 -31.55 -38.83 10Y US Treasury 2.799 -1.059 -0.665

S&P Mib 16263 -41.02 -48.29 30Y US Treasury 3.744 -0.629 -0.567

Swiss SMI 4970.38 -28.44 -31.30 10Y UK Gilt 3.271 -1.285 -1.161

Nikkei 225 8636.33 -29.37 -33.47 10Y CH Govt Bond 2.188 -0.570 -0.688

Australia AORD 3586.3 -28.52 -33.79

HK Hang Seng 14114.2 -28.06 -39.36 Money Markets Last % Ch 6M % Ch 12M

Shanghai Comp. 2361.704 -0.26 -36.87 US 6M Depo 1.775 -2.101 -0.857

Singapore StraitT. 1756.45 -30.79 -43.61 EUR 6M Depo 1.705 -3.585 -3.013

India BSE30 9855.75 -28.64 -40.39 GBP 6M Depo 1.92875 -4.429 -4.041

Brazil Bovespa 41799.3 -19.35 -31.74 CHF 6M Depo 0.54667 -2.450 -2.365

Russia RTSI 750.42 -43.22 -62.84 JPY 6M Depo 0.7775 -0.244 -0.245


MArKEts ViEW

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